Flow direction algorithm for optimal coordination of directional overcurrent relays considering arc flash by Dina K. Mahmoud, Shady H．E．Abdel Aleem, Ahmed M. Ibrahim, Mahmoud M. Sayed, Wael Abdelfattah

“…The effectiveness of the FDA method is verified by comparing it with well-known methods such as Gravitational Search Algorithm, Imperialistic Competition Algorithm, Sine Cosine Algorithm, and Harmony Search Algorithm. …”
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Intelligent Layout Method of Ship Pipelines Based on an Improved Grey Wolf Optimization Algorithm by Yongjin Lu, Kai Li, Rui Lin, Yunlong Wang, Hairong Han

“…The improved algorithm has better global search ability, higher solution stability, and faster convergence speed than the standard grey wolf optimization algorithm. …”
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Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation by Krzysztof Lamorski, Cezary Sławiński, Felix Moreno, Gyöngyi Barna, Wojciech Skierucha, José L. Arrue

“…Alternative to previous attempts known from literature, the ν-SVM method was used for model development and the results were compared with the formerly used the C-SVM method. For the purpose of models’ parameters search, genetic algorithms were used as an optimisation framework. …”
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Artificial Intelligence With Neural Network Algorithms in Pediatric Astrocytoma Diagnosis: A Systematic Review by Floresya K. Farmawati, Della W.A. Nurwakhid, Tifani A. Pradhea, Rayyan Fitriasa, Hutami H. Arrahmi, Muhana F. Ilyas, Fadhilah T. Nur

“…The search strategy was guided by a PECO question focusing on pediatric astrocytoma diagnosis using AI algorithms vs computed tomography or magnetic resonance imaging (MRI). …”
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Application of Improved Electromagnetism-like Mechanism Algorithm on Massive Remote Sensing Image Screening by Yingjie Fang, Kun Liu, Xun Zhang, Gang Lin, Huibing Wang, Lina Dong, Su Li

“…Compared with the original algorithm, it can search for the global optimal solution more quickly and has better robustness.…”
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An efficient binary salp swarm algorithm for user selection in multiuser MIMO antenna systems by A. Sasikumar, Logesh Ravi, Malathi Devarajan, Abdulaziz S. Almazyad, Shuvodeep De, Guojiang Xiong, Seyed Jalaleddin Mousavirad, Ali Wagdy Mohamed

“…Due to their high computational cost, many user selection methods currently in use, such as greedy algorithms and exhaustive search are unsuitable for MU-MIMO systems. …”
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An Improved Crayfish Algorithm-Based Neural Network Method for Modeling Microstrip Patch Antennas by Shao-Long Cao, Yu Shao, Yang Wang, Ju Tan, Jie Zhang

“…The improved algorithm was evaluated on standard test functions, demonstrating superior convergence speed and accuracy compared to other algorithms. …”
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A Multiobjective Particle Swarm Optimization Algorithm Based on Competition Mechanism and Gaussian Variation by Hongli Yu, Yuelin Gao, Jincheng Wang

“…The simulation experiment results show that the improved algorithm has better convergence and stability than the other compared algorithms.…”
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An FPGA Task Placement Algorithm Using Reflected Binary Gray Space Filling Curve by Senoj Joseph Olakkenghil, K. Baskaran

“…In the proposed FPGA model, the CLBs are numbered according to reflected binary gray space filling curve model. The search algorithm will quickly identify a placement for the incoming task based on first fit mode or a fragmentation aware best fit mode. …”
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A Neural Network: Family Competition Genetic Algorithm and Its Applications in Electromagnetic Optimization by P.-Y. Chen, C.-H. Chen, H. Wang

“…The NN-FCGA is a hybrid evolutionary-based algorithm, combining the good approximation performance of neural network (NN) and the robust and effective optimum search ability of the family competition genetic algorithms (FCGA) to accelerate the optimization process. …”
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An Enhanced Differential Evolution Based Algorithm with Simulated Annealing for Solving Multiobjective Optimization Problems by Bili Chen, Wenhua Zeng, Yangbin Lin, Qi Zhong

“…The proposed algorithm utilizes the advantage of simulated annealing for guiding the algorithm to explore more regions of the search space for a better convergence to the true Pareto-optimal front. …”
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Pregnancy probability prediction models based on 5 machine learning algorithms and comparison of their performance by REN Chao, REN Chao, YANG Huan, ZHOU Niya, ZHOU Niya

“…In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions, feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set. Five algorithms, that is, Logistic Regression, Naive Bayes, Random Forest, Gradient Boosting Machine, and Support Vector Machine, were used to construct preconception outcome prediction models, and the parameters of each model were optimized using random search combined with grid search. …”
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Image Reconstruction Algorithm Based on Spectral Projected Gradient Pursuit for Electrical Capacitance Tomography by WANG Li-li, LIU Hong-bo, CHEN De-yun, CHEN Feng

“…Simulation experiment of typical flow pattern is carried out by the algorithm，and compared with the traditional LBP algorithm. …”
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A Sufficient Descent 3-Term Conjugate Gradient Method for Unconstrained Optimization Algorithm by Ghada Moayid Al-Naemi, Samaa AbdulQader

“…Despite the fact that the BRB algorithm achieved global convergence by employing a modified strong Wolfe line search, in this new MTTBRB-CG method the researchers employed the classical strong Wolfe-Powell condition (SWPC). …”
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Analysis of student’s final qualification theses using text loans detection systems by D. A. Petrusevich, K. D. Shakhardin

“…It seems that these differences can be explained with different text search and analyze algorithms. The dependencies between the Rucontext percentage and the Antiplagiat text loan percentage is presented.…”
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Enhanced genetic algorithm for indoor low-illumination stereo matching energy function optimization by Zhang Hongjin, Wei Hui

“…The algorithm utilizes a novel biomimetic mutation strategy, dynamically adjusted through common allelic theory, to effectively reduce the search space and improve optimization efficiency. …”
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Research on bearing fault diagnosis based on improved northern goshawk algorithm optimizing SVM by WU Xiaojun, LI Quwei

“…In order to evaluate the performance of the improved algorithm, firstly, benchmark testing functions were used for experiments, and the improved algorithm was compared with existing optimization algorithms such as NGO, particle swarm optimization (PSO), sparrow search algorithm (SSA), etc. …”
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A Bidirectional-RRT*-Connect-Assisted RRT*-Smart for a path planning algorithm by Heru Suwoyo, Yudi Hastomi, Julpri Andika

“…The goal is to replace the RRT* algorithm to produce a more optimal initial formed path. …”
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Prediabetes risk classification algorithm via carotid bodies and K-means clustering technique by Rafael F. Pinheiro, Maria P. Guarino, Marlene Lages, Rui Fonseca-Pinto

“…Diabetes is a disease that affects millions of people in the world and its early screening prevents serious health problems, also providing relief in the demand for healthcare services. In the search for methods to support early diagnosis, this article introduces a novel prediabetes risk classification algorithm (PRCA) for type-2 diabetes mellitus (T2DM), utilizing the chemosensitivity of carotid bodies (CB) and K-means clustering technique from the field of machine learning. …”
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Low-Complexity LDPC Decoding Algorithm Based on Layered Vicinal Variable Node Scheduling by Mhammed Benhayoun, Mouhcine Razi, Anas Mansouri, Ali Ahaitouf

“…The informed dynamic scheduling (IDS) strategies for the low-density parity check (LDPC) decoding have shown superior performance in error correction and convergence speed, particularly those based on reliability measures and residual belief propagation (RBP). However, the search for the most unreliable variable nodes and the residual precomputation required for each iteration of the IDS-LDPC increases the complexity of the decoding process which becomes more sequential, making it hard to exploit the parallelism of signal processing algorithms available in multicore platforms. …”
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