Risk Assessment of Supplier R&D Investment Based on Improved BP Neural Network by Yinghua Song, Xiaoyan Sang, Zhe Wang, Hongqian Xu

“…By leveraging the ability of particle swarm optimization (PSO), whale optimization algorithm (WOA), and genetic algorithm (GA) to search for global optimal solutions, the BP neural network is improved to avoid becoming trapped in local optimal solutions and enhance the model’s generalization ability. …”
Get full text

Dual-Resource Scheduling with Improved Forensic-Based Investigation Algorithm in Smart Manufacturing by Yuhang Zeng, Ping Lou, Jianmin Hu, Chuannian Fan, Quan Liu, Jiwei Hu

“…In the first stage, an improved multi-objective FBI algorithm is used to obtain the Pareto front solutions of this model, in which a hybrid real and integer encoding–decoding method is used for exploring the solution space and a fast non-dominated sorting method for improving efficiency. …”
Get full text

Energy management strategy for hybrid electric vehicle based on improved PPO algorithm by Chao MA, Tong SUN, Lei CAO, Kun YANG, Wenjing HU

“…In order to improve the economy of power-split hybrid electric vehicle (HEV),a longitudinal dynamics model of the entire HEV vehicle was established,and an energy management strategy (EMS) based on strategy entropy optimization with an improved proximal policy optimization (PPO) algorithm was proposed. …”
Get full text

Research on Particle Swarm Optimization-Based UAV Path Planning Technology in Urban Airspace by Qing Cheng, Zhengyuan Zhang, Yunfei Du, Yandong Li

“…In this study, an improved particle swarm optimization algorithm (LGPSO) is proposed to address these problems. …”
Get full text

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

“…This paper proposes an improved crayfish optimization algorithm (ICOA) to optimize the initial weights and biases of the neural network, aiming to enhance both convergence accuracy and speed. …”
Get full text

New Improved Fractional Order Differentiator Models Based on Optimized Digital Differentiators by Maneesha Gupta, Richa Yadav

“…Different evolutionary algorithms (EAs), namely, particle swarm optimization (PSO), genetic algorithm (GA), and PSO-GA hybrid optimization, have been used to optimize digital differential operators so that these can be better fitted to exemplify their new improved fractional order differentiator counterparts. …”
Get full text

An improved meta-heuristic algorithm to optimize the fractional-order controller for an industrial manipulator with a parallelogram structure by Nazila Nikdel

“…Therefore, this article pursues two main objectives: 1) controlling the robotic system by presenting a method based on fractional-order calculus so that it can control the system despite its complexity and non-linearity, 2) presenting the meta-heuristic algorithm "Improved Grey Wolf" to optimize the system response.Methodology: First, the mathematical model of the robot is presented based on Lagrange rules, and then the fractional-order calculus is used to design the controller. …”
Get full text

Optimal Active-Reactive Power Dispatch for Distribution Network With Carbon Trading Based on Improved Multi-Objective Equilibrium Optimizer Algorithm by Furong Tu, Sumei Zheng, Kuncan Chen

“…Then proposed an improved multi-objective equilibrium optimizer (IMOEO) algorithm for solving the OARPD problem with renewable generators. …”
Get full text

A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
Get full text

Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

“…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
Get full text

Recognition algorithm of piano playing music notes based on improved hidden Markov model by Ziwei Wang

“…The recognition process of piano playing music notes is affected by low-frequency components, resulting in suboptimal features that affect recognition accuracy. Therefore, an improved hidden Markov model based recognition algorithm for piano playing music notes is proposed. …”
Get full text

Path Planning for Construction Robot Based on the Improved A* Algorithm and Building Information Modeling by Dejiang Wang, Bolong Liu, Haili Jiang, Panpan Liu

“…Finally, the improved A* algorithm is employed to perform path planning within the environment map generated from the BIM model, resulting in the generation of the optimal path. …”
Get full text

Diagnosis model for action problems of table tennis beginners based on improved DTW algorithm by Zhiguo Xin

“…To enhance the skills of beginners, a diagnosis model for table tennis beginner movement problems based on sensors and an improved dynamic time-warping algorithm is proposed. …”
Get full text

Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

“…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
Get full text

Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

“…To address this challenge, we propose a novel prediction model that integrates an adaptive-weight particle swarm optimization (AWPSO) algorithm with a back propagation neural network (BPNN). …”
Get full text

Hybrid stochastic and robust optimization of a hybrid system with fuel cell for building electrification using an improved arithmetic optimization algorithm by Fude Duan, Mahdiyeh Eslami, Mustafa Okati, Dheyaa J. Jasim, Arsalan Khadim Mahmood

“…The study utilizes an improved arithmetic optimization algorithm (IAOA) to optimize component sizes and MRUs, incorporating a neighborhood search operator to enhance performance and prevent premature convergence. …”
Get full text

Research on Fractional-Order Control of Anchor Drilling Machine Optimized by Intelligent Algorithms by Jingkai Li, Jun Zhang, Jiaquan Xie, Wei Shi, Jianzhong Zhao

“…To achieve precise docking in unmanned conditions, we employed an inner-loop fractional-order proportional–integral–derivative (FOPID) controller optimized by an improved particle swarm optimization (ILPSO) algorithm. …”
Get full text

Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
Get full text

An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

“…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
Get full text

An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
Get full text