Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Among the available methods, partial transmit sequence (PTS) is an efficient PAPR reduction method but can be computationally expensive while deter-mining optimal phase factors (OPFs). Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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An Optimal Longitudinal Control Strategy of Platoons Using Improved Particle Swarm Optimization by Zhizhou Wu, Zhibo Gao, Wei Hao, Jiaqi Ma

“…An improved particle swarm optimization algorithm was used to optimize the weighting coefficients for the controller state and control variables. …”
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Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Our implementation tests show that leveraging these new concepts of mtDNA and Continental Model results in relative improvement of the optimization quality of GA.…”
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IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems by Fang Li, Congteng Dai, Abdelazim G. Hussien, Rong Zheng

“…The Parrot Optimizer (PO) is a new optimization algorithm based on the behaviors of trained Pyrrhura Molinae parrots. …”
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A low-carbon scheduling method based on improved ant colony algorithm for underground electric transportation vehicles by Yizhe Zhang, Yinan Guo, Yao Huang, Shirong Ge

“…To solve this problem, an improved ant colony optimization algorithm integrated with Q-learning (ACO-QL) is proposed. …”
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Optimization method of obstacle avoidance path for dual-arm cooperative robot based on machine vision by Jing Li

“…An improved bat algorithm is employed to optimize the obstacle avoidance path of the dual-arm cooperative robot, ultimately yielding the optimal path. …”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…To achieve high efficiency and high power density designs, it is essential to study core loss characteristics and optimize operating parameters. This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Improvement of reading platforms assisted by the spring framework: A recommendation technique integrating the KGMRA algorithm and BERT model by Yawen Su

“…To address these limitations, this study introduces a novel recommendation system that combines the Knowledge Graph-based Multi-Relational Association (KGMRA) algorithm with the Bidirectional Encoder Representations from Transformers (BERT) model. …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…The variables are microgrid optimal location and capacity of the HMG components in the network which are determined through a multi-objective improved Kepler optimization algorithm (MOIKOA) modeled by Kepler’s laws of planetary motion, piecewise linear chaotic map and using the FDMT. …”
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Ultra Short-Term Charging Load Forecasting Based on Improved Data Decomposition and Hybrid Neural Network by Shaoyang Yin, Zhaohui Chen, Wanyuan Liu, Zhiwen Su

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Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm by Bo Gao, Xiangjun Li, Fang Guo, Xiping Wang

“…The Time Delay Second Estimation (TDSE) algorithm optimized the improved Transformer model to overcome traditional models’ limitations in extracting long-term dependency. …”
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SAHAANN: A NOVEL EVOLUTIONARY ARTIFICIAL NEURAL NETWORK FOR IMPROVED FINANCIAL TIME SERIES FORECASTING by Abdul Khadeer, Vanaparthi Kiranmai, B. Suvarnamukhi, Ayaz Mohiuddin, Balika Mahesh, P M Suresh, J Arthy, Sasikumar A N, Sudersan Behera, Mohd Ayaz Uddin

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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

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Determining Appropriate Strategy for Managing the Energy Production System in the Presence of Renewable Energy Sources and Improved Intelligence Method by Amir Sohel, Md Faisal Bin Ashab

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OptiSGD-DPWGAN: Integrating Metaheuristic Algorithms and Differential Privacy to Improve Privacy-Utility Trade-Off in Generative Models by Alshaymaa Ahmed Mohamed, Yasmine N. M. Saleh, Ayman A. Abdel-Hamid

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A Low-Carbon Scheduling Method for Container Intermodal Transport Using an Improved Grey Wolf–Harris Hawks Hybrid Algorithm by Meixian Jiang, Shuying Lv, Yuqiu Zhang, Fan Wu, Zhi Pei, Guanghua Wu

“…The model is solved using an improved grey wolf–Harris hawks hybrid algorithm (IGWOHHO). …”
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System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario by Wenhao Luo, Yuan Zeng, Ximeng Zheng, Lingyan Zha, Weicheng Cai, Qing Wang, Jingjin Zhang

“…Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. …”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Ultra-Short-Term Wind Power Forecasting Based on the MSADBO-LSTM Model by Ziquan Zhao, Jing Bai

“…Incorporating an improved Sine Algorithm (MSA) into the forecasting model for this nonlinear problem significantly improves the position update strategy of the Dung Beetle Optimization Algorithm (DBO), which tends to be overly random and prone to local optima. …”
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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…To address the issue of rolling bearing fault diagnosis, this paper proposes a novel model combining the Improved Gorilla Troop Optimization (IGTO) algorithm, Variational Mode Decomposition (VMD), Permutation Entropy (PE), and Long Short-Term Memory (LSTM) networks. …”
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