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Article
Computer Science, Artificial Intelligence
Hardi Mohammed et al.
Summary: This paper presents a novel nature-inspired optimization algorithm, the Fox optimizer (FOX), which imitates the foraging behavior of foxes in nature. The algorithm effectively jumps by measuring the distance between the fox and its prey. The performance of FOX is evaluated using benchmark functions and compared against various other optimization algorithms, demonstrating its superiority.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Farhad Soleimanian Gharehchopogh et al.
Summary: Mathematical programming and meta-heuristics are two types of optimization methods. Meta-heuristic algorithms mimic natural behaviors to identify optimal solutions and have benefits such as simplicity, few parameters, avoidance of local optimization, and flexibility. This paper reviews the sparrow search algorithm, a new and robust algorithm for optimization, covering its variants, improvement, hybridization, and optimization.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Farhad Soleimanian Gharehchopogh
Summary: Metaheuristic algorithms are efficient solutions for optimization problems, and quantum-inspired metaheuristic algorithms, which integrate quantum computing concepts, can achieve better results in solving complex optimization problems. Quantum computing plays a crucial role in enhancing the performance of metaheuristic algorithms.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Ya Shen et al.
Summary: In this work, a multi-population evolution based variant of the whale optimization algorithm (MEWOA) is proposed to solve the slow convergence and local optimum problems. MEWOA divides individuals into three sub-populations and assigns different moving strategies to each sub-population, performing global and local search. The introduction of a novel population evolution strategy further enhances MEWOA's global optimization ability. Experimental results demonstrate the competitiveness and merits of MEWOA, achieving faster convergence speed, shorter runtime, and higher solution accuracy compared to other algorithms on benchmark functions and real-world problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Farhad Soleimanian Gharehchopogh et al.
Summary: Meta-heuristic algorithms, such as the Slime Mould algorithm (SMA), play a significant role in solving optimization problems in various fields. SMA, inspired by the fluctuating behavior of slime mold, utilizes adaptive weights and a unique mathematical model to provide optimal solutions. This paper examines SMA's application in hybridization, progress, changes, and optimization, with usage rates ranging from 7% to 42%. The repeated use of SMA in solving optimization problems signifies its practicality and potential benefits for engineers, professionals, and academic scientists.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Mehdi Ayar et al.
Summary: This study introduces a chaotic-based method for feature selection, enabling quick and automatic diagnosis and classification of cardiac arrhythmias with high accuracy and time efficiency.
JOURNAL OF SUPERCOMPUTING
(2022)
Article
Computer Science, Information Systems
Saeid Talebpour Shishavan et al.
Summary: This paper improves the Cuckoo Search Optimization (CSO) algorithm for community detection in complex networks using a Genetic Algorithm (GA) to address issues with premature convergence and local optimal trap. By dynamically adjusting population size and utilizing modularity objective function and Normalized Mutual Information, the proposed algorithm outperforms basic comparative algorithms in terms of modularity and NMI. Average performance enhancements of 54% in modularity and 88% in NMI are achieved compared to other algorithms.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Nitish Chopra et al.
Summary: The Golden Jackal Optimization (GJO) algorithm, inspired by the hunting behavior of golden jackals, utilizes prey searching, enclosing, and pouncing steps mathematically to solve challenging engineering problems with unidentified search spaces.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Jayashree Piri et al.
Summary: This article introduces a novel discrete artificial gorilla troop optimization (DAGTO) technique for feature selection tasks in the healthcare sector. The presented method is proven to be superior in identifying relevant features and is demonstrated to be effective in real-world applications through a case study with COVID-19 samples.
Article
Multidisciplinary Sciences
Sabat Abdulhameed et al.
Summary: The CDDO algorithm, inspired by children's learning behavior and cognitive development, uses the golden ratio to optimize beauty in art, showing superior performance in optimizing problems and competitively scoring 2.8 ranks in comparison to other state-of-the-art algorithms.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Chnoor M. Rahman et al.
Summary: In this article, a novel evolutionary algorithm called learner performance based behavior algorithm (LPB) is proposed, drawing inspiration from the process of accepting graduated learners from high school in different departments at university in order to optimize their studying behaviors and improve their study level. The proposed LPB algorithm outperformed DA, GA, and PSO in most cases, showcasing its ability to handle large optimization problems and improve the initial population towards global optima.
EGYPTIAN INFORMATICS JOURNAL
(2021)
Article
Mathematical & Computational Biology
Ashish Sharma et al.
Summary: Bone cancer is a serious health issue that often leads to patient death. Automated systems are needed to classify and identify cancerous bone. Choosing the right edge detection algorithm and feature set is crucial for the performance of machine learning models.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE
(2021)
Article
Oncology
Wen-Cai Liu et al.
Summary: The study aimed to establish a machine learning prediction model for bone metastasis in newly diagnosed thyroid cancer patients. A total of 17,138 patients were included, with 166 (0.97%) developing bone metastases. The RF model had better predictive performance compared to other models, with an AUC of 0.917, accuracy of 0.904, recall rate of 0.833, and specificity of 0.905.
Article
Mathematics
Deeam Najmadeen Hama Rashid et al.
Summary: A novel swarm intelligent algorithm, the ant nesting algorithm (ANA), inspired by Leptothorax ants, mimics ant behavior to optimize problems. The algorithm outperforms prominent metaheuristic algorithms on test functions and real-world engineering problems, showcasing its competitive capabilities.
Review
Medicine, General & Internal
Qiuhan Zheng et al.
Summary: This study evaluated the diagnostic accuracy of AI algorithms in detecting tumor metastasis using medical radiology imaging. The results showed that AI algorithms may perform as well as or even better than healthcare professionals in terms of sensitivity and specificity. Different AI algorithms, such as machine learning and deep learning, showed varying levels of sensitivity and specificity.
Article
Engineering, Electrical & Electronic
Hekmat Mohammadzadeh et al.
Summary: This paper proposes a new method called MAS as Metaheuristic (MAMH) method, which combines multi-agent systems and metaheuristic algorithms to effectively solve high-dimensional optimization problems. The binary version of the proposed method, called Binary MAMH (BMAMH), also demonstrates higher precision in email spam detection compared to other metaheuristic algorithms and methods.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Mohammed M. Nasef et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2020)
Article
Computer Science, Artificial Intelligence
Yong Zhang et al.
APPLIED INTELLIGENCE
(2019)
Review
Mathematical & Computational Biology
Hardi M. Mohammed et al.
COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
(2019)
Article
Radiology, Nuclear Medicine & Medical Imaging
Florina-Gianina Elfarra et al.
ANNALS OF NUCLEAR MEDICINE
(2019)
Article
Computer Science, Information Systems
Jaza Mahmood Abdullah et al.
Article
Engineering, Chemical
Ihsan Salman et al.
Article
Engineering, Biomedical
Annika Liebgott et al.
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
(2018)
Article
Computer Science, Interdisciplinary Applications
Seyedali Mirjalili et al.
ADVANCES IN ENGINEERING SOFTWARE
(2016)
Proceedings Paper
Computer Science, Theory & Methods
Madhuri Avula et al.
ASIA MODELLING SYMPOSIUM 2014 (AMS 2014)
(2014)
Article
Oncology
RE Coleman
CANCER TREATMENT REVIEWS
(2001)
