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Article
Computer Science, Interdisciplinary Applications
Abdelazim G. Hussien et al.
Summary: This study proposes an enhanced variant of the whale optimization algorithm (WOA) called VCSWOA, which combines components from other algorithms. The comprehensive testing and comparison with other algorithms demonstrate that VCSWOA outperforms its peers in terms of performance.
ENGINEERING WITH COMPUTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Hongliang Zhang et al.
Summary: This paper presents a chaotic SSA with differential evolution (CDESSA) to improve the convergence speed and accuracy of the salp swarm algorithm (SSA) in handling complex optimization problems. Experimental results demonstrate that CDESSA performs significantly better than the original SSA and other compared methods in solving real-parameter optimization and engineering optimization problems.
ENGINEERING WITH COMPUTERS
(2023)
Article
Biology
Jianfu Xia et al.
Summary: A new parameter optimization strategy based on DFSCA is proposed and integrated into KELM to establish DFSCA-KELM, improving optimization performance. Experimental results demonstrate the effectiveness of the model in medical diagnosis.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Thermodynamics
Anouar Farah et al.
Summary: The demand for renewable energy has increased due to the environmental impact and scarcity of fossil fuels. To accurately model photovoltaic cells, a comprehensive learning Rao-1 (CLRao-1) optimization algorithm is proposed, achieving the best results in terms of reliability and accuracy.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Thermodynamics
Youssef Kharchouf et al.
Summary: This study proposes an improved differential evolution technique using the Lambert W function and a meta-heuristic step to select optimal parameters. By applying it to various solar photovoltaic cells and modules, the method has shown significant advantages in reducing computation time and enhancing convergence characteristics.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Engineering, Electrical & Electronic
Xiaoqin Zhang et al.
Summary: Single image dehazing is a fundamental and challenging task in computer vision, and has gained significant attention. Existing haze-removal methods often suffer from issues such as degraded visual quality and color distortions. To address these issues, we propose a network with multi-scale hierarchical feature fusion and mixed convolution attention, which enhances the dehazing performance progressively and adaptively.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Bin Cao et al.
Summary: In this article, a novel neural network model is proposed by integrating gene expression programming into the interval type-2 fuzzy rough neural network, aiming to generate more expressive fuzzy rules. The network training is treated as a multiobjective optimization problem to consider network precision, explainability, and generalization simultaneously. An enhanced distributed parallel multiobjective evolutionary algorithm is introduced to explore different forms of fuzzy rules and improve precision and convergence.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zonghui Cai et al.
Summary: This paper proposes a grid-based search operator (GBS) to improve the exploration capability of Brain Storm Optimization (BSO). Modification of the cluster, replacement, and mutation strategy is also introduced to enhance exploitation. An alternate search pattern (ASP) strategy is designed to balance exploration and exploitation. The proposed variants ABSO and AGBSO show improved performance in solution quality and population diversity compared to the original BSO.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jiao Hu et al.
Summary: The dispersed foraging slime mould algorithm (DFSMA) is proposed as an enhanced version of the slime mould algorithm (SMA) to address the limitations of SMA in solving multimodal and hybrid functions. Experimental results demonstrate that DFSMA outperforms other algorithms in terms of convergence speed and accuracy. Furthermore, the binary DFSMA (BDFSMA) is evaluated and found to have improved performance in classification accuracy and feature selection compared to other optimization algorithms.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Kangjia Qiao et al.
Summary: The paper introduces a self-adaptive resources allocation-based differential evolution (SRADE) to balance diversity, convergence, constraints, and objective function in addressing constrained optimization problems. By dynamically assigning different mutation strategies to individuals based on their performance feedback, the method effectively improves search efficiency under limited resources by focusing on the most efficient strategy.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Optics
Sudan Yu et al.
Summary: In this paper, a new method combining gradient-based optimization with orthogonal learning is proposed for parameter estimation in solar photovoltaic models. Experimental results demonstrate that the method improves both accuracy and speed.
Article
Biology
Jianfu Xia et al.
Summary: This research aimed to construct a new intelligent diagnostic method that is accurate, fast, noninvasive, and cost-effective in distinguishing between complicated and uncomplicated appendicitis. The study analyzed the data of 298 patients with acute appendicitis and identified the most significant variables, then built a diagnostic model using an improved grasshopper optimization algorithm-based support vector machine.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biology
Qiu Guan et al.
Summary: In this paper, a new medical image augmentation method called TMP-GAN is proposed, which utilizes joint training of multiple channels, adversarial learning-based texture discrimination loss, and progressive generation mechanism to improve the quality of synthesized images for lesion detection. Experimental results show that the detector trained on the TMP-GAN augmented dataset outperforms other data augmentation methods in terms of precision, recall, and F1-score.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Review
Biology
Yizhou Chen et al.
Summary: This paper provides a comprehensive review and analysis of medical image augmentation, focusing on the advantages of different augmentation models, loss functions, and evaluation metrics. It explores the potential role of augmented models in limited training set scenarios and discusses the limitations and research directions in this field. The research shows that this field is still actively developing.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Automation & Control Systems
Helong Yu et al.
Summary: This paper introduces the issues and shortcomings of Grey Wolf Optimizer (GWO) and proposes an improved version called Multi-Stage Grey Wolf Optimizer (MGWO). By dividing the search process into three stages and using different population updating strategies, MGWO improves optimization ability while maintaining a certain convergence speed. It has a better balance of exploration and exploitation, can avoid getting trapped in local optima, and obtains higher-quality solutions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: This study presents the analysis and principle of an innovative optimizer called INFO, which utilizes the weighted mean method to optimize different problems. The results show that INFO outperforms other methods in terms of exploration and exploitation, and is capable of converging to satisfactory solutions in engineering problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Liquan Zhao et al.
Summary: This article proposes an encoder-decoder method based on generative adversarial network to address the problem of remote sensing image dehazing. The method learns image features using low-frequency and high-frequency information, and incorporates skip connections, multi-scale attention module, CBlock module, and distillation module to enhance the dehazing ability of the network. Experimental results demonstrate that this method achieves the best performance on the RICE dataset, both qualitatively and quantitatively.
IEEE SENSORS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Sudan Yu et al.
Summary: This paper proposes an efficient sine cosine differential gradient-based optimization method for identifying unknown parameters of photovoltaic models. The method combines the sine cosine strategy and the mutation crossover of the differential evolution algorithm to avoid local optima and achieve the minimal root mean square error. The simulation results demonstrate its potential in estimating photovoltaic model parameters.
IET RENEWABLE POWER GENERATION
(2022)
Article
Computer Science, Information Systems
Wu Deng et al.
Summary: This paper proposes an enhanced fast NSGA-II algorithm (ASDNSGA-II) for solving multi-modal multi-objective optimization problems. By using a special congestion strategy and adaptive crossover strategy, ASDNSGA-II improves the distribution and convergence of solutions. Experimental results show that ASDNSGA-II can effectively find the global Pareto solution set and improve the distribution and convergence of solutions.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Liping Huang et al.
Summary: This paper proposes a context-aware road travel time estimation framework using trajectory data and third-order tensor modeling, combined with congestion levels and points of interest information to fill missing data and calculate the final travel time matrix. The effectiveness of the method was validated on two real-world datasets, showing superior accuracy performance compared to state-of-the-art methods.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Information Systems
Sen Qiu et al.
Summary: This paper proposes an automatic phase segmentation method combined with a machine learning algorithm for analyzing kayak rowing. The results indicate that the combination of arm to trunk joint angle and support vector machine algorithm can better complete the task of phase segmentation.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Construction & Building Technology
Dongmin Yu et al.
Summary: This paper proposes a new regret analysis method called stochastic p-robust optimization (SPRO) technique, which combines the advantages of stochastic optimization (SO) and robust optimization (RO) approaches for optimal operation of hybrid energy systems. The numerical results show that the proposed approach can effectively reduce the maximum relative regret of the system operator while increasing the HES operation cost.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Computer Science, Information Systems
Zongda Wu et al.
Summary: This paper proposes a method to protect user privacy in LBS by constructing dummy query sequences to conceal user query locations and attributes, effectively protecting location privacy and attribute privacy.
WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS
(2021)
Article
Energy & Fuels
Sameh Selem et al.
Summary: This paper discusses a new approach by AEFA to define uncertain model parameters for TDM of PV units, utilizing intensive simulations and analysis to validate the parameters based on empirical data points. Performance assessments were conducted to compare AEFA results with others, alongside dynamic simulations of MPP.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Prashant Malik et al.
Summary: The study developed a new integrated single-diode solar cell model for predicting PV power generation, with experimental validation showing an error range of 4.29% to 4.76% compared to measured values. Different parameter models showed varying accuracy in power prediction under different solar irradiance levels.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Jing Liang et al.
Summary: In this paper, a rankings-based fitness function method is designed for efficiently selecting and utilizing promising infeasible solutions in solving constrained optimization problems using evolutionary algorithms. The method dynamically adjusts weights to balance constraints and objectives, and generates promising offspring using three differential evolution strategies. Experimental results show the proposed method's superior performance compared to other state-of-the-art methods, especially in solving real-world problems.
APPLIED SOFT COMPUTING
(2021)
Article
Thermodynamics
Mohamed Abdel-Basset et al.
Summary: This paper proposes an improved algorithm based on the marine predators algorithm for extracting optimal values of photovoltaic parameters. Experimental results demonstrate the superior performance of the proposed algorithm compared to existing algorithms on photovoltaic models.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Thermodynamics
Wei Zhou et al.
Summary: The proposed RLGBO algorithm improves the GBO method for parameter identification in photovoltaic models by introducing a random learning mechanism, effectively increasing accuracy and convergence speed. Its performance is validated in various commercial photovoltaic models, demonstrating accuracy in parameter estimation under different environmental conditions.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Mahmoud M. Elkholy et al.
Summary: This study developed an effective tool based on artificial ecosystem optimizer (AEO) to define uncertain parameters of PV generating units, with validations through experiments and statistics. Results showed that AEO produced best values with lesser RMSDs compared to other optimizers for different solar technologies.
IET RENEWABLE POWER GENERATION
(2021)
Article
Computer Science, Artificial Intelligence
Yutao Yang et al.
Summary: The research proposes a population-based optimization technique called Hunger Games Search (HGS), designed based on the hunger-driven activities and behavioral choices of animals, with a simple structure, special stability features, and competitive performance to efficiently address constrained and unconstrained problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Wenfeng Zheng et al.
Summary: This paper constructs a knowledge base graph embedding module to extend the versatility of knowledge-based VQA models. By extracting core entities from images and text and performing sub-graph embedding, the accuracy of knowledge-based VQA models is improved.
PATTERN RECOGNITION
(2021)
Article
Computer Science, Artificial Intelligence
Jiao Hu et al.
Summary: This research introduces an enhanced variant of the GWO algorithm named GWOCMALOL, which outperforms other algorithms in terms of convergence speed and accuracy, showing better performance in solving complex problems.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Wenfeng Zheng et al.
Summary: This paper proposes a multi-layer semantic representation network for sentence representation, which enhances the accuracy and comprehensiveness of sentence representation through multi-attention mechanism and relative position mask.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Bin Cao et al.
Summary: In order to address the growing problem of traffic pollution caused by the rapid increase in motor vehicles, a many-objective optimization model of multi-depot heterogeneous vehicle CARP is constructed in this study. Through the use of a memetic algorithm based on Two_Arch2, the model is effectively optimized and the pollution problem is successfully solved.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Information Systems
Bin Cao et al.
Summary: An improved RFID reader anticollision model is proposed in this article, utilizing intelligent computing technologies and distributed parallel cooperative co-evolution particle swarm optimization to address the high-dimensional problem of dense deployment of large numbers of readers.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Mohamed H. Hassan et al.
Summary: The modified gradient-based optimizer (MGBO) is proposed to improve performance in estimating the parameters of Photovoltaic models. MGBO accelerates convergence rate and avoids local optima, making it suitable for nonlinear optimization problems like Photovoltaic model parameters estimation. The results show that MGBO has fast conversion rate and precision compared to other algorithms in solving the optimization problem.
Review
Automation & Control Systems
Yicun Hua et al.
Summary: This paper provides a comprehensive survey of research on solving multi-objective optimization problems with irregular Pareto fronts, covering basic concepts, benchmark test problems, analysis of irregularity causes, real-world optimization problems, existing methodologies, representative algorithms, strengths, weaknesses, open challenges, and future directions.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
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
Thermodynamics
Jingbo Wang et al.
Summary: The novel improved equilibrium optimizer proposed in this paper enhances photovoltaic cell datasets using neural networks and improves optimization performance by allocating different selection probabilities for equilibrium candidates based on fitness values. Compared to the original method, the improved optimizer achieves higher optimization precision and reliability.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Thermodynamics
Mohamed Abd Elaziz et al.
Summary: The paper proposes an enhanced marine predators algorithm (EMPA) to identify unknown parameters for different photovoltaic (PV) models, showing superior performance in both static and dynamic PV models.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Iman Ahmadianfar et al.
Summary: The optimization field is plagued by metaphor-based pseudo-novel or fancy optimizers, with limited contributions to the optimization process. This study introduces a novel metaphor-free population-based optimization method called RUNge Kutta optimizer (RUN) based on mathematical foundations, showing promising results in mathematical tests and engineering problems. The RUN algorithm utilizes slope variations computed by the RK method for global optimization, demonstrating superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Leila Esmaeili et al.
Summary: A novel image thresholding method, based on an improved human mental search algorithm, is proposed in this paper to address the time complexity issue of the minimum cross-entropy approach. Extensive experiments demonstrate the competitive performance of the proposed algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Zhenan He et al.
Summary: A novel knee-based decision-making method is proposed to search for solutions of interest from a large number of solutions on the Pareto front, ensuring the performance of these solutions approximates as much as possible the whole Pareto front. Additionally, a new visualization approach is developed to provide information about the shape, location, possible bulge, convergence degree, and distribution of solutions on MaOPs.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Engineering, Civil
Bin Cao et al.
Summary: Researched diversified recommendation problems in the Internet of Vehicles and constructed a multi-objective recommendation model, considering not only recommendation precision but also recommendation novelty and coverage.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Energy & Fuels
Attia A. El-Fergany
Summary: This paper investigates the characterization of PV units and the extraction of model parameters, using the slime mould algorithm and its improved version to achieve the goal, demonstrating good results in two test cases.
Article
Computer Science, Artificial Intelligence
Zongda Wu et al.
Summary: This paper proposes a method to protect users' commodity viewing privacy by constructing dummy requests on a trusted client to confuse and cover up user preferences on the untrusted server-side. The study introduces a privacy model and an implementation algorithm to measure the effectiveness of confusion and cover-up effects. The results show that the proposed approach effectively enhances the security of users' commodity viewing privacy on the untrusted server-side.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Bin Cao et al.
Summary: This paper proposes a many-objective optimization model for optimizing the deployment of drone-assisted cameras based on a 3D terrain environment. An improved algorithm outperforms state-of-the-art algorithms in the experimental results.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Thermodynamics
Xuemeng Weng et al.
Summary: The enhanced spherical evolution algorithm, incorporating Laplace's cross search mechanism and the Nelder-Mead simplex method, is proposed for identifying unknown parameters in PV models. The algorithm aims to improve the accuracy and efficiency in evaluating PV model parameters compared to other existing algorithms.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Computer Science, Artificial Intelligence
Sheng-Hao Wu et al.
Summary: The proposed SAFE method is a novel approach to efficiently solve expensive optimization problems by using a set of evaluation methods with different accuracy scales. Experimental results demonstrate that the method achieves better solution quality compared to baseline and state-of-the-art algorithms.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Engineering, Civil
Bin Cao et al.
Summary: The development of the Internet of Vehicles has brought about intelligent network transportation systems. This paper studied the placement problem of Edge Servers (ESs) in the IoV and constructed a six-objective ES deployment optimization model. By optimizing the deployment problem of ESs using a many-objective evolutionary algorithm, the effectiveness of the algorithm and model was verified through comparisons with state-of-the-art methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Engineering, Civil
Zhihan Lv et al.
Summary: This study aims to improve the intelligent transportation system using deep learning algorithms, leading to enhanced data transmission performance, accurate prediction, and effective path adjustment strategy to suppress congestion spread.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Guoxi Liang et al.
Summary: Automated essay scoring is an exciting task in natural language processing where researchers have been exploring the detection of creative essays. This paper proposes a method using a generative adversarial network framework to judge the creativity of essays by masking part of the content. Experimental results show the feasibility of the proposed approach in identifying creative essays.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Ruyi Dong et al.
Summary: The Kernel Search Optimization (KSO) algorithm was proposed to simplify the optimization process by transforming the optimization of nonlinear functions into a linear process. By adopting a local search of the hill-climbing algorithm and simplifying the calculation of kernel parameters, the improved algorithm outperformed the original KSO and some well-known algorithms in terms of accuracy and running time.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Suvita Rani Sharma et al.
Summary: The paper proposes a hybrid SFO-TLBO algorithm integrating sunflower optimization and teaching-learning-based optimization to achieve a balance between global exploration and convergence speed. The hybrid algorithm outperforms twelve state-of-the-art algorithms in benchmark tests and shows superior performance in solving an Internet of Vehicles optimization problem when compared with fifteen algorithms. Additionally, a binary version of the hybrid SFO-TLBO algorithm is proposed for feature selection, achieving an average accuracy of 89.10% in classification tasks.
Article
Energy & Fuels
Prashant Malik et al.
Summary: The study predicts power generation of a photovoltaic power plant using a new solar cell model that accounts for aging module degradation. The accuracy of the model is validated under different solar irradiance ranges, showing higher accuracy in low irradiance and improved precision in medium to high ranges. The results suggest that the model can accurately predict the real output power of a PV system after including degradation, with potential for further research in identified areas.
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
Computer Science, Artificial Intelligence
Ye Tian et al.
Summary: This paper proposes an evolutionary multi-objective optimization approach for disease module identification, which constructs sample-specific networks to involve personalized features, and optimizes module association with disease and intra-link density using a genetic algorithm. The approach outperforms existing methods in identifying disease modules and leads to lower classification error rates in disease classification experiments.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2021)
Article
Engineering, Multidisciplinary
Jiaze Tu et al.
Summary: This paper introduces a new stochastic optimizer called the Colony Predation Algorithm (CPA) based on the predation behavior of animals in nature, utilizing mathematical mapping to improve algorithm performance by simulating strategies used by animal hunting groups. The proposed CPA demonstrates competitive performance in optimizing engineering problems and will provide publicly available source code after publication.
JOURNAL OF BIONIC ENGINEERING
(2021)
Article
Computer Science, Information Systems
Wenfeng Zheng et al.
Summary: In visual reasoning, deep learning has greatly improved the accuracy of results. By introducing semantic representation, a higher-level representation, more accurate results can be obtained. This study lays the foundation for introducing different levels of knowledge representation into deep learning in the future.
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(2020)
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Biochemical Research Methods
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IEEE TRANSACTIONS ON NANOBIOSCIENCE
(2020)
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Zongda Wu et al.
KNOWLEDGE-BASED SYSTEMS
(2020)
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Hongliang Zhang et al.
ENERGY CONVERSION AND MANAGEMENT
(2020)
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Hussein Mohammed Ridha et al.
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(2020)
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Yanan Sun et al.
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(2020)
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Jun Li et al.
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(2020)
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Da Gao et al.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2020)
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Xu Chen et al.
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(2020)
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IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2020)
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(2019)
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INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
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Deyu Tang
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(2019)
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(2019)
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(2019)
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Wei-Chang Yeh et al.
IET RENEWABLE POWER GENERATION
(2018)
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Zhile Yang et al.
KNOWLEDGE-BASED SYSTEMS
(2018)
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Donghui Wang et al.
KNOWLEDGE-BASED SYSTEMS
(2018)
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COGNITIVE SYSTEMS RESEARCH
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INTERNATIONAL JOURNAL OF COMPUTER VISION
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(2014)
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(2012)
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