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Article
Computer Science, Artificial Intelligence
Yiying Zhang et al.
Summary: Most metaheuristic methods require control parameters for optimal solution. Group teaching optimization algorithm (GTOA) is a new method that optimizes using only the essential population size and terminal condition. This paper proposes a new variant of GTOA, called ISGTOA, which enhances communication between outstanding and average groups by reusing individuals. Experimental results demonstrate the superiority of ISGTOA for complex optimization problems.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Gehad Ismail Sayed
Summary: Image segmentation is an important task for extracting useful information from an image. In this paper, a new hybrid algorithm based on quantum computing and optimal foraging algorithm is presented for multilevel image segmentation. The proposed algorithm achieves a proper balance between exploration and exploitation phases by integrating quantum operators and the optimization process of the optimal foraging algorithm.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Engineering, Multidisciplinary
Vahid Goodarzimehr et al.
Summary: This paper presents a new hybrid algorithm, PSOGA, to optimize space trusses with continuous design variables. The hybridization of PSO and GA algorithms improves the efficiency and robustness of the algorithm in both exploration and exploitation. The algorithm has been tested and compared with other researchers by solving benchmark problems.
WORLD JOURNAL OF ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Abdullah M. Shaheen et al.
Summary: This article proposes an enhanced quasi-reflection jellyfish optimization algorithm for solving the optimal power flow problem. The algorithm balances exploration and exploitation by introducing quasi-opposition-based learning and reflecting social groups among the population. Multiple experiments have verified the quality and resilience of the proposed solution.
ENGINEERING OPTIMIZATION
(2023)
Article
Computer Science, Hardware & Architecture
M. Usharani et al.
Summary: Approximate computing is a popular field for low power consumption in applications like image processing and data mining. Designing low power approximate multipliers is challenging, but combining deep learning methods with meta-heuristics optimization techniques can improve accuracy and reduce error rates.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Tanmay Kundu et al.
Summary: This paper proposes a novel optimization algorithm, HSSATLBO, for solving reliability redundancy allocation problems (RRAP) with nonlinear resource constraints. By improving the salp swarm algorithm (SSA) with the teaching-learning based optimization (TLBO) algorithm, the HSSATLBO algorithm achieves better exploration and exploitation capabilities. Experimental results demonstrate that HSSATLBO outperforms other algorithms in solving various benchmark reliability optimization problems.
APPLIED INTELLIGENCE
(2022)
Review
Computer Science, Interdisciplinary Applications
Hossam Ashraf et al.
Summary: This paper evaluates the importance of mathematical modeling and parameter identification in proton exchange membrane fuel cell systems and provides a comprehensive review of meta-heuristic algorithms applied in this field. The article introduces the classification and characteristics of these algorithms and summarizes various PEMFC models and evaluation criteria. This research is significant for future studies and improvements.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2022)
Article
Construction & Building Technology
Jui-Sheng Chou et al.
Summary: The MOFBI algorithm utilizes chaotic maps and elite populations to explore and exploit multi-objective search spaces, providing more accurate approximations of Pareto-optimal solutions compared to other algorithms.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Anurag Tiwari et al.
Summary: The widespread use of feature selection in various fields emphasizes its importance in expert and intelligent systems. Conventional methods suffer from poor classification accuracy and high computational cost, while hybrid methods offer better efficiency and scalability. A new hybrid feature selection method, IFS-DBOIM, was introduced to address these issues, showing improved performance in classification accuracy with fewer features.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Alisan Ayvaz et al.
Summary: This paper proposes a novel optimization method for wind power investment that considers the economic and security aspects of power system operation and planning. It achieves a balance between system security and economic efficiency by considering the uncertainties of wind power.
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY
(2022)
Article
Computer Science, Artificial Intelligence
Saeid Barshandeh et al.
Summary: This paper presents a novel Learning-Automata (LA)-based hybrid optimization algorithm for global optimization problems. The algorithm modifies the artificial Jellyfish search algorithm and Marine Predator Algorithm to reduce computational complexity while retaining their strengths. The LA mechanism is used to intelligently select the most optimal action for updating particles. Experimental results demonstrate the superiority of the proposed LA-based hybrid algorithm in solving benchmark functions and data clustering problems.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Construction & Building Technology
Jui-Sheng Chou et al.
Summary: This study proposes a method that combines deep learning and bio-inspired optimization to measure the deflection of reinforced concrete beams. The hybrid model achieves higher accuracy than traditional models and provides insights in similar visual surveillance tasks.
STRUCTURAL CONTROL & HEALTH MONITORING
(2022)
Article
Telecommunications
S. Selvakumar et al.
Summary: This paper discusses the issue of spectrum fragmentation in Elastic Optical Networks (EON) and proposes a new algorithm, PR-DF-JFSO, to address spectrum management problems. Experimental results show that this algorithm performs well, improves spectrum utilization and network efficiency, and reduces connection blocking rate.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Engineering, Multidisciplinary
Jitendra Rajpurohit et al.
Summary: Nature inspired optimization algorithms are effective tools for problem-solving. This paper proposes a method to enhance the performance of Jellyfish Search Optimizer (JSO) through the implementation of chaotic maps. The results show that the Sinusoidal map outperforms other chaotic maps and JSO in terms of efficiency and accuracy.
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2022)
Review
Computer Science, Artificial Intelligence
Shuo Meng et al.
Summary: This paper provides a comprehensive review of recent research on automatic recognition of woven fabric structural parameters, highlighting the drawbacks of manual operations based on human eyes and experiences and the advantages of computer-vision-based automatic methods. It offers insights for researchers in the textile industry to understand and utilize automated methods effectively.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Anil Kumar Dsouza et al.
Summary: This manuscript proposes an intelligent hybrid approach for managing power flow in smart grid systems. It combines the Nomadic People Optimizer (NPO) algorithm with the artificial transgender longicorn algorithm (ATLA) to control power flow in hybrid renewable energy systems. The approach is implemented in MATLAB and compared with existing methods to evaluate its performance.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Mathematics, Interdisciplinary Applications
K. Aravind et al.
Summary: In the Internet of Things, multicast transmission is used to distribute messages to specific nodes or objects, with geographic-based multicast routing schemes playing a crucial role in remote healthcare services. However, existing models have certain disadvantages.
Article
Engineering, Multidisciplinary
Hoda Zamani et al.
Summary: This paper presents a novel bio-inspired algorithm called SMO, which mimics the behaviors of starlings during their stunning murmuration, to solve complex engineering optimization problems. The SMO introduces dynamic multi-flock construction and three new search strategies, achieving competitive results in solution quality and convergence rate compared to other state-of-the-art algorithms.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Gang Hu et al.
Summary: The paper proposes an enhanced arithmetic optimization algorithm (CSOAOA) that addresses the limitations of the original AOA in large-scale applications. CSOAOA incorporates strategies such as point set initialization, optimal neighborhood learning, and crisscross optimization to improve the overall performance of AOA. Experimental results demonstrate the superiority of CSOAOA in terms of precision, convergence rate, and solution quality.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohamed Abdel-Basset et al.
Summary: This paper investigates the high-dimensional 0-1 knapsack instances and transforms five meta-heuristic algorithms into binary ones. Genetic operators are used to further improve the results. The experimental findings show that BIRFSO performs exceptionally well for instances with dimensions greater than 500.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Thermodynamics
Abdullah M. Shaheen et al.
Summary: This paper investigates the Combined Heat and Power Economic Dispatch (CHPED) problem and proposes a new optimization method AHJFO, which combines the characteristics of Heap-based Optimizer (HO) and Jellyfish Optimizer (JFO) to improve the effectiveness of the solution. The proposed method shows superior performance in solving the CHPED problem for medium and large systems.
Article
Computer Science, Information Systems
Xinming Zhang et al.
Summary: This paper proposes an improved SL-PSO algorithm, called TLS-PSO, which enhances the optimization performance of PSO through the use of three learning strategies and a hybrid learning mechanism. Experimental results demonstrate that TLS-PSO outperforms state-of-the-art PSO variants and other algorithms on complex functions and engineering problems, indicating its superior performance and potential for practical problem-solving.
INFORMATION SCIENCES
(2022)
Article
Engineering, Multidisciplinary
Mehmet Bahadir cetinkaya et al.
Summary: Biomedical image analysis based on metaheuristic algorithms is an important research area. Effective methods are required to diagnose diseases with high accuracy in high-contrast biomedical images. Metaheuristic approaches, with their advantages of converging to the global optimum, higher convergence rate, and fewer control parameters, can offer effective solutions in this field.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Computer Science, Information Systems
Soner Kiziloluk et al.
Summary: This study proposes an early hurricane detection method called Hurricane-Faster R-CNN-JS, which achieves a higher accuracy compared to other methods by optimizing model parameters.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Engineering, Civil
Ali Kaveh et al.
Summary: This paper introduces a new framework for reliability-based design optimization using metaheuristic algorithms based on decoupled methods. The efficiency of the proposed framework is improved by introducing new reliability assessment methods and termination conditions.
Article
Thermodynamics
Rolla Almodfer et al.
Summary: This study predicts the performance of a solar thermoelectric air-conditioning system using advanced optimized artificial intelligence models. The experimental data and optimized models show high accuracy, with RVFL-JFSA model recommended for modeling the STEACS system.
CASE STUDIES IN THERMAL ENGINEERING
(2022)
Article
Water Resources
Riham Ezzeldin et al.
Summary: In this study, a simulation-optimization model based on the artificial Jellyfish Search algorithm is developed for sustainable saltwater intrusion management in coastal aquifers. The model is tested using real aquifer systems and compared with other optimization algorithms, demonstrating its efficiency and effectiveness.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2022)
Article
Computer Science, Interdisciplinary Applications
Sarunyoo Boriratrit et al.
Summary: Electric energy demand forecasting is crucial for electric utilities to ensure sufficient and reliable supply for consumers. This study proposes a method that combines metaheuristic optimization with ELM to improve accuracy and reduce overfitting in forecasting models. Experimental results show that the JS-ELM model provides the lowest root mean square error with an appropriate processing time.
Article
Dana Marsetiya Utama et al.
Bulletin of Electrical Engineering and Informatics
(2022)
Article
Computer Science, Artificial Intelligence
Ahmad Eid
Summary: This paper optimizes the allocation of DG and SC devices to minimize a multi-objective problem and achieves significant savings in energy loss through the adoption of the Jellyfish Search Algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Jianzhou Wang et al.
Summary: This study aims to establish an integrated interval forecasting system for solar radiation, using feature extraction and a hybrid kernel relevance vector machine. The proposed system achieves higher coverage rate and narrower interval width in solar radiation forecasting.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Construction & Building Technology
Jui-Sheng Chou et al.
Summary: Reinforced concrete shear walls are commonly used in seismic structures, and modern building codes have provisions for shear capacity. However, existing provisions may have limitations, and rational methods can be used as an alternative to predict shear wall capacity. In this study, data-driven machine learning models are trained and optimized using metaheuristic algorithms to achieve the best results. This approach improves building safety, simplifies calculation processes, and reduces material costs.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Telecommunications
L. Raja et al.
Summary: This paper proposes a trusted distributed routing scheme for wireless sensor networks using blockchain and Jelly Fish Search Optimizer algorithm to improve network efficiency and security. By optimizing the weight parameters of the Deep Generative Adversarial Neural Network, while reducing black hole problems and attackers, the proposed approach achieves higher network performance.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Mathematical & Computational Biology
Yang Lei et al.
Summary: This paper proposes an improved jellyfish search optimizer grey model for predicting rural resident income in Shaanxi Province. By enhancing the algorithm and model, better performance is achieved, providing reliable forecast data.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Mathematical & Computational Biology
Jui-Sheng Chou et al.
Summary: This study uses deep learning models to predict the compressive strength of concrete. By comparing computer vision and conventional numerical data methods, it is found that computer vision methods outperform the traditional methods in terms of accuracy and reliability. The computer vision models were further optimized using a bio-inspired metaheuristic algorithm, resulting in the best prediction models.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2022)
Article
Engineering, Multidisciplinary
Abdullah Shaheen et al.
Summary: This article presents a new implementation of the Artificial Ecosystem Optimizer (AEO) technique for distributed generators (DGs) and capacitors allocation in power distribution systems. The AEO algorithm is compared with other optimization techniques, and results show its superiority in optimizing network performance.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
Mohamed Assaad Hamida et al.
Summary: In this paper, an artificial hummingbird optimization technique (AHOT) is proposed to identify the unknown parameters of Li-Ion batteries used in electric vehicles. The AHOT simulates the flying abilities and foraging tactics of hummingbirds, and its effectiveness and efficiency are demonstrated through comparison with other techniques.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Shubham et al.
International Journal of Ambient Energy
(2022)
Article
B. E. Nyong-Bassey et al.
Nigerian Journal of Technology
(2022)
Article
Construction & Building Technology
Dinh-Nhat Truong et al.
Summary: This paper presents a novel fuzzy adaptive jellyfish search-optimized stacking system that demonstrates high accuracy and effectiveness in global optimization and engineering informatics.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Energy & Fuels
Dong-Dong Yuan et al.
Summary: An improved Jellyfish Search algorithm optimization support vector regression (IJS-SVR) model is proposed in this study to achieve high-precision wind power prediction. The model shows better prediction results in spring and winter compared to other models, improving the prediction accuracy of wind power. This study provides an economical and effective method to address the uncertainties of wind power.
Article
Energy & Fuels
Jui-Sheng Chou et al.
Summary: Plant microbial fuel cells (PMFCs) are an emerging green-energy technology. An artificial intelligence model using deep learning techniques and an optimization algorithm was developed to accurately forecast the power generation capacity of PMFCs. The model can also estimate the future power generation capacity of PMFC devices.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Ashraf Fathy Ali et al.
Summary: This paper presents an effective optimal sizing technique for a hybrid Microgrid using an artificial Jellyfish Search optimizer. The proposed method aims to meet demand while minimizing load disturbance, resulting in optimal cost and improved system reliability.
2022 4TH ASIA ENERGY AND ELECTRICAL ENGINEERING SYMPOSIUM (AEEES 2022)
(2022)
Article
Mathematics, Applied
Lamiaa M. El Bakrawy et al.
Summary: This study proposes a modified antlion optimization (MALO) algorithm to improve the primary antlion optimization algorithm (ALO) for the task of instance reduction. The results show that the MALO algorithm outperforms the basic ALO algorithm and other comparative algorithms in terms of convergence rate and performance measures like Accuracy, Balanced Accuracy (BACC), Geometric mean (G-mean), and Area Under the Curve (AUC). The MALO algorithm offers a potential solution to the problem of local optima stagnation and slow convergence speed.
Article
Computer Science, Information Systems
Tummala. S. L. V. Ayyarao et al.
Summary: This paper proposes a metaheuristic optimization algorithm based on ancient war strategy, which achieves a good balance between exploration and exploitation stages by simulating the strategic movements of army troops during war. The algorithm introduces a novel weight updating mechanism and a weak soldier's relocation strategy to improve its convergence and robustness.
Article
Mathematics, Applied
Jui-Sheng Chou et al.
Summary: This study introduces a novel metaheuristic algorithm, JS optimizer, inspired by the behavior of jellyfish. The algorithm outperforms ten well-known metaheuristic algorithms in solving mathematical benchmark functions and structural optimization problems. JS has the potential to be an excellent algorithm for solving optimization problems.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Thermodynamics
Eid A. Gouda et al.
Summary: This paper presents a novel attempt to use the Jellyfish search algorithm (JSA) for solving the parameters' identifications problem of polymer exchange membrane fuel cells (PEMFCs) model. Through three test cases, the JSA is demonstrated to effectively optimize the fitness function and achieve the best cropped values of SSEs. The JSA proves its ability to handle the problem competently compared to others, with maximum percentage voltage biased error within +/-1% in all test cases.
Article
Mathematics, Interdisciplinary Applications
Xiaodan Liang et al.
Summary: In this study, a multistrategy enhanced version of SMA called ESMA was proposed to overcome the shortcomings of the basic SMA algorithm. Three enhanced strategies, including chaotic initialization strategy, orthogonal learning strategy, and boundary reset strategy, were utilized to improve the performance of ESMA. Experimental results showed that ESMA outperformed other state-of-the-art algorithms, indicating that the three strategies significantly enhanced the performance of the basic SMA algorithm.
DISCRETE DYNAMICS IN NATURE AND SOCIETY
(2021)
Article
Thermodynamics
Abdullah M. Shaheen et al.
Summary: The article introduces an enhanced multi-objective Quasi-Reflected Jellyfish Search Optimizer (MOQRJFS) for solving multi-dimensional Optimal Power Flow (MDOPF) issue. With two modifications to strengthen the searching capability of JFS algorithm, the MOQRJFS is applied to various systems and proven to be superior.
Article
Thermodynamics
Mohamed Abdel-Basset et al.
Summary: The study introduces an improved chimp optimization algorithm (IChOA) for defining uncertain parameters of proton exchange membrane fuel cells (PEMFC), achieving better modeling accuracy and performance optimization through a ranking-based updating strategy and a balanced exploration and exploitation strategy. The proposed IChOA is compared with 15 nature-inspired metaheuristics algorithms and a gradient-based optimizer, demonstrating superior convergence stability and final accuracy under varied conditions.
Article
Multidisciplinary Sciences
Emad T. Elkabbash et al.
Summary: Smartphone usage is widespread worldwide, with Android leading as the open-source operating system of choice. Malicious actors target Android due to its large user base. A novel detection system, RVFL+JS, was introduced to optimize classification performance for malicious apps.
Article
Green & Sustainable Science & Technology
Afroz Alam et al.
Summary: This article discusses the significance of the energy crisis and solar photovoltaic systems in addressing energy demands. It also highlights the challenges in maximum power point tracking and partial shading conditions faced by PV systems.
Article
Energy & Fuels
Mohamed Abdel-Basset et al.
Summary: This study introduces a modified artificial jellyfish search optimizer (MJSO) with a premature convergence strategy (PCS) to define parameter values for PV systems. Numerical simulations confirm the algorithm's superiority in accuracy and convergence rate.
Article
Automation & Control Systems
Dalia Yousri et al.
Summary: This paper proposes a novel approach to enhance the exploratory behavior of the Harris hawks optimizer based on fractional calculus memory concept, resulting in the fractional-order modified Harris hawks optimizer (FMHHO). The sensitivity of algorithm performance to FOC parameters is addressed, with the best variant recommended based on benchmarks. The proposed variant is validated using CEC2017 benchmarks and compared to other techniques through statistical measures and non-parametric tests, showing improved performance and accurate solutions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Jui-Sheng Chou et al.
Summary: A weighted-feature least squares support vector regression model optimized by the jellyfish search algorithm was developed to predict the peak friction angle of fiber-reinforced soil. Analytical results showed that the model outperformed other models in the literature and identified new feature combinations with higher accuracy.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Nimra Idris Siddiqui et al.
Summary: This paper introduced an artificial jellyfish search algorithm for voltage control in multilevel inverters, aiming to eliminate lower-order harmonics in the output waveform. By applying the algorithm to CHB-MLI with different levels and modulation indexes, it outperformed the DE and GA algorithms in terms of total harmonic distortion reduction. Experimental results confirmed the superior performance of the AJFS algorithm.
Article
Construction & Building Technology
Nhat-Duc Hoang et al.
Summary: In this study, a computer vision-based method is developed for automatic classification of concrete spalling severity. The method uses texture descriptors and a support vector machine classifier to distinguish between shallow and deep spalling accurately.
ADVANCES IN CIVIL ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Ly Huu Pham et al.
Summary: This paper proposes a High Performance Cuckoo Search Algorithm (HPCSA) for determining suitable operation parameters of the optimal wind-hydro-thermal system scheduling (OWHTSS) problem, and experiments show that it outperforms other methods in terms of cost, stability, search speed, and success rate.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
Article
Energy & Fuels
Dalia Yousri et al.
Summary: This paper introduces an improved metaheuristic approach of comprehensive learning marine predator algorithm (CLMPA) to identify optimal parameters of supercapacitor equivalent circuit. By utilizing the principle of comprehensive learning strategy, the proposed approach shares best experiences among all particles to avoid immature convergence.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Electrical & Electronic
Ali Durmus et al.
Summary: This paper investigates the optimization problem in antenna array design, comparing the performance of several swarm-based metaheuristic algorithms, with results showing that the novel algorithms MA and JS outperform the traditional PSO and ABC methods.
JOURNAL OF COMPUTATIONAL ELECTRONICS
(2021)
Article
Chemistry, Multidisciplinary
Erica Ocampo et al.
Summary: The PSPSO introduces a two-fold searching mechanism to increase the search capability of Particle Swarm Optimization, avoiding premature convergence and simplifying communication among particles. Results show the effectiveness of PSPSO in comparison with published PSO variants.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Benyamin Abdollahzadeh et al.
Summary: Metaheuristics, especially the African Vultures Optimization Algorithm (AVOA), play a crucial role in solving optimization problems, outperforming existing algorithms in standard benchmarks and engineering design problems. The statistical evaluation further confirms the significant superiority of AVOA.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Thermodynamics
Jui-Sheng Chou et al.
Summary: The study combines energy-saving with intelligent systems, using smart grids to manage power distribution and consumption, improving future energy consumption prediction accuracy through deep learning technology, ultimately establishing a hybrid JS-CNNs model to optimize energy management and supply.
Article
Thermodynamics
Dalia Yousri et al.
Summary: This article investigates the use of the triple diode model (TDM) for modeling various PV modules and introduces a novel hybrid algorithm called HMPA. Results demonstrate that HMPA outperforms other algorithms in identifying TDM parameters, as confirmed by statistical analysis and convergence curves.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Khaled Nusair et al.
Summary: This article introduces four new independent, reliable and efficient optimization algorithms inspired by nature and biological nature, for solving OPF problems in modern power network models, including different operation cases considering stochastic renewable energy sources and FACTS. The new metaheuristic optimization techniques are more effective solvers for OPF problems compared to PSO, GWO and MFO algorithms.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Ahmed T. Salawudeen et al.
Summary: This paper presents an extensive study of a new metaheuristics algorithm called Smell Agent Optimization (SAO) on CEC numerical optimization benchmark functions and Hybrid Renewable Energy System (HRES) engineering problems. Results show that SAO excels in finding global optimum solutions and cost-effective designs, outperforming benchmarked algorithms.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Ahmed Ginidi et al.
Summary: The article presents a novel approach to parameter extraction for solar photovoltaic systems using Gorilla Troops Optimization (GTO) technique, showing its effectiveness through numerical analysis of PV models. Comparison with other algorithms in 2020 demonstrates the superiority of GTO in terms of standard deviations of fitness values. Validation of GTO for diverse operating conditions of KC200GT module further confirms its efficacy.
Article
Mathematics
Ahmed Ginidi et al.
Summary: This paper introduces a hybrid algorithm, HBJSA, that combines the strengths of HBA and JSA to solve CHP economic dispatch issues, showcasing superior performance in experimentation compared to standard algorithms.
Proceedings Paper
Automation & Control Systems
Heba Youssef et al.
Summary: A new application of the Jellyfish search optimizer algorithm (JS) is proposed in this study to estimate the parameters of single-phase power transformer, demonstrating its effectiveness through experimental verifications.
2021 IEEE IFAC INTERNATIONAL CONFERENCE ON AUTOMATION/XXIV CONGRESS OF THE CHILEAN ASSOCIATION OF AUTOMATIC CONTROL (IEEE IFAC ICA - ACCA2021)
(2021)
Proceedings Paper
Automation & Control Systems
Ghaith Manita et al.
Summary: The jellyfish search optimizer (JSO) has been widely used to solve real-world optimization problems, but faces challenges in exploration and exploitation search. This paper introduces a new variant, OJSO, based on orthogonal learning to enhance global searching capability. Evaluation shows that the proposed algorithm outperforms the original algorithm in all aspects except execution time.
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021)
(2021)
Article
Computer Science, Information Systems
Bing Ma et al.
Summary: This paper proposes a novel series of SSA variants by combining SSA with improved Tent chaos mutation, Levy flights mutation, elite opposition-based learning mutation, variable radius mutation, and their combinations. The performance of these variants is evaluated on 31 benchmark test functions and real-world constrained engineering problems, demonstrating superior performance compared to state-of-the-art optimization algorithms.
Article
Computer Science, Information Systems
Andi Tang et al.
Summary: The Manta ray foraging optimization (MRFO) is a novel swarm-based metaheuristic optimizer but has drawbacks such as random selection of reference points and chain foraging. To address these issues, a modified version m-MRFO is proposed using strategies like elite search pool, adaptive control parameter, and distribution estimation. The performance of m-MRFO was validated on various test functions and real-world problems, showing significant improvements over MRFO.
Article
Computer Science, Information Systems
Mohamed Farhat et al.
Summary: Today's electrical power system faces challenges such as power losses, voltage instability, and line overloads. Optimizing real and reactive powers through installing energy resources can minimize losses and improve voltage profiles. The optimal power flow problem is considered a crucial tool for efficient electricity production and reliable power system operation.
Article
Computer Science, Information Systems
Ahmed R. Ginidi et al.
Summary: The study examines the application of heap-based optimization algorithm (HBOA) in cogeneration systems economic dispatch (CSED), considering transmission losses and valve point impacts. Results show that HBOA performs significantly well in large-scale systems compared to other optimizers.
Article
Computer Science, Information Systems
Abdullah M. Shaheen et al.
Summary: The article introduces a new application of the Forensic-Based Investigation Algorithm (FBIA) to accurately extract the electrical parameters of different PV models, which is validated through numerical analysis.
Article
Computer Science, Information Systems
Mohamed H. Hassan et al.
Summary: The optimal planning of reactive power is crucial for increasing system efficiency and maintaining voltage under acceptable values.
Article
Energy & Fuels
Jui-Sheng Chou et al.
Summary: This study developed a novel forecasting system that optimizes linear time-series with nonlinear machine learning models to identify historical patterns of regional energy consumption. The system was found to accurately predict energy consumption ahead of time with high efficiency in numerical experiments, demonstrating its potential application in efficiently dispatching regional energy capacity for sustainable cities.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
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ARTIFICIAL INTELLIGENCE REVIEW
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ARTIFICIAL INTELLIGENCE REVIEW
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Mathematics, Interdisciplinary Applications
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CHAOS SOLITONS & FRACTALS
(2020)
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Jui-Sheng Chou et al.
APPLIED SOFT COMPUTING
(2020)
Article
Computer Science, Theory & Methods
Shimin Li et al.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2020)
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Thermodynamics
Tae-Young Kim et al.
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Mathematics, Applied
Iztok Fister et al.
APPLIED MATHEMATICS AND COMPUTATION
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Biochemistry & Molecular Biology
Sabrina Fossette et al.
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Marine & Freshwater Biology
Thomas Bastian et al.
ESTUARINE COASTAL AND SHELF SCIENCE
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Mathematics, Applied
A. H. Gandomi et al.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
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Review
Ecology
Sabrina Fossette et al.
MARINE ECOLOGY PROGRESS SERIES
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Review
Chemistry, Medicinal
Gian Luigi Mariottini et al.
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Environmental Sciences
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MARINE POLLUTION BULLETIN
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Letter
Medicine, General & Internal
K Landow
POSTGRADUATE MEDICINE
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