A novel feature selection algorithm using decomposition based multi-objective guided honey badger algorithm (MO-GHBA) and NSGA-III by Anusha Papasani, Nagaraju Devarakonda

“…In most of the MOEAs based feature selection algorithms, more optimal solutions are obtained around the Pareto front's center because of the deficiency in selection features. …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…This framework synergistically integrates an optimized bidirectional hierarchical gated recurrent unit (BiHGRU), a Transformer encoder, and a novel Greenness and Water Content Composite Index, with critical parameters optimized by particle swarm optimization (PSO). …”
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Optimizing laser powder bed fusion parameters for enhanced hardness of Ti6Al4V alloys: A comparative analysis of metaheuristic algorithms for process parameter optimization by Praveenkumar V, Vijaykumar S. Jatti, Saiyathibrahim A, Praveen Kumar D, Murali Krishnan R, Vinaykumar S. Jatti, A. Johnson Santhosh

“…Given its simplicity alongside its accuracy and robust performance, the JAYA algorithm proves the most appropriate method for LPBF parameter optimization. …”
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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…Corn is one of the most important global agricultural commodities, contributing to food, feed, and fuel production. …”
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SIMULATION ANALYSIS AND OPTIMIZATION OF AIR SUSPENSION SYSTEM OF A LIGHT COMMERCIAL VEHICLE (MT) by WANG Lei, HUANG ZhaoMing, LI HaiYu, CHEN Tian

“…The simulation results of ride comfort after optimization show that: under random input, the root mean square value of weighted acceleration at the driver is reduced by 13.6%, and that at the passenger is reduced by 25.6%; under pulse input, the maximum vertical acceleration at the driver is reduced by 15.9%, and that at the passenger is reduced by 29.4%, and the ride comfort of the whole vehicle is significantly improved.…”
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Enhanced multi-level K-means clustering and cluster head selection using a modernized pufferfish optimization algorithm for lifetime maximization in wireless sensor networks by Anjana Koyalil, Sivacoumar Rajalingam

“…This optimization enhances the network coverage, data acquisition efficiency, and energy conservation, ultimately prolonging the network lifetime and improving overall system reliability. …”
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Mathematical Modeling of Cyberattack Defense Mechanism Using Hybrid Transfer Learning With Snow Ablation Optimization Algorithm in Critical Infrastructures by Mohamad Khairi Ishak

“…In addition, the snow ablation optimization (SAO) algorithm can be exploited for the optimum choice of feature subsets. …”
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Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous by Faezeh Borhani, Majid Shafiepour Motlagh, Amir Houshang Ehsani, Yousef Rashidi, Alireza Noorpoor, Saeid Maddah

“…According to the optimization results, the most suitable air temperature and percent excess air were selected to achieve the lowest pollutant emissions. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
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An optimal neural network to design generators and stabilizers for multi-machine power systems based on a promoted firefly algorithm by Xiujun Nie, Nan Sun, Buqin Wang, Ganbar Akbari

“…The network has been optimized by a new promoted version of the firefly algorithm for PSS design and the parameters of this controller in a number of specific working conditions in a multi-machine power system. …”
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Optimizing Traffic Speed Prediction Using a Multi-Objective Genetic Algorithm-Enhanced RNN for Intelligent Transportation Systems by C. Swetha Priya, F. Sagayaraj Francis

“…Additionally, we developed a Multi-Objective Genetic Algorithm (MOGA)-enhanced RNN model to optimize hyperparameters and achieve accurate traffic speed predictions. …”
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Global optimization of economic load dispatch in large scale power systems using an enhanced social network search algorithm by Mohamed H. Hassan, Salah Kamel, Francisco Jurado, Umberto Desideri

“…The primary goal is to improve the algorithm's ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. …”
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Multi-objective optimization and parameter sensitivity study on microreactor nuclear power systems by Ersheng You, Yiyi Li, Jianjun Xu, Dianchuan Xing, Haochun Zhang

“…The PSO algorithm code was used to calculate and compare the benchmark case of MRNPS, and the optimized Pareto optimal solution set was obtained. …”
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A Novel Modified Gorilla Troops Optimizer Algorithm for Interline Power Flow Controller-Based Damping Controller Design by Rajendra Kumar Khadanga, Deepa Das, Sidhartha Panda, Soumya Ranjan Mahapatro, Manoj Kumar Kar, Ahmed Al Mansur, Taha Selim Ustun, Akhtar Kalam

“…Based on the simulation results, the updated strategy that has been suggested is the most effective way to define the mentioned damping controller by considering the percentage improvement in the goal function value.…”
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Optimization of Structural Parameters and Cavitation Suppression in Control Valves Based on P-WOA by W. Li, S. Li, J. Hou, L. Yang, Y. Tian

“…Boosting method integrates reinforcement learning PPO with the whale optimization algorithm (WOA) to form the P-WOA model. …”
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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…The grid-connected SMG consists of photovoltaic (PV) cells, BSS, and residential loads. A Genetic Algorithm (GA)-based method is proposed to optimize power management in three scenarios: (i) active power only (AOM), (ii) active and reactive power without line losses (ARM), and (iii) active and reactive power considering line losses (ARLM). …”
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An intelligent framework for sarcasm detection in Arabic tweets using deep learning with Al-Biruni earth radius optimization algorithm by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Wafa Sulaiman Almukadi, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

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Priority Load Management for Improving Supply Reliability of Critical Loads in Healthcare Facilities Under Highly Unreliable Grids by Ndukwe Henry Ibiam, Fadi Kahwash, Jubaer Ahmed

“…It was found that the priority-based algorithm improved the reliability served to the most critical loads at the expense of the least critical. …”
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Improving Event Data in Football Matches: A Case Study Model for Synchronizing Passing Events with Positional Data by Alberto Cortez, Bruno Gonçalves, João Brito, Hugo Folgado

“…Three datasets were used to perform this study: a dataset created by applying a custom algorithm that synchronizes positional and event data, referred to as the optimized synchronization dataset (OSD); a simple temporal alignment between positional and event data, referred to as the raw synchronization dataset (RSD); and a manual notational data (MND) from the match video footage, considered the ground truth observations. …”
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