Improved Genetic Algorithm of Helical Gear Reducer and 3D Modeling by Hao Liping

“…Based on the penalty function method combined with the improved genetic algorithm,the multi-objective and multi-restriction reliability optimal design of the reducer with hardened tooth surface and modified helical cylinder gear is carried out.According to the properties of the constraint conditions,the different methods are used for effectively avoiding the local optimum problem.The accurate three-dimensional description of the involute gear is carried out by the establishment of the tooth profile curve coordinate equation of the involute gear.According to the interface technology of VB and SolidWorks,the three-dimensional parametric modeling of the involute gear is achieved based on the optimal design results.…”
Get full text

Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

“…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
Get full text

Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm by Changbiao Zhu, Chongxin Wang, Zhonghua Ni, Xiaojun Liu, Abbas Raza

“…Applying an ant colony (ACO) algorithm to solve the production scheduling problem achieved the intelligent scheduling and optimization of production tasks. …”
Get full text

Optimization based machine learning algorithms for software reliability growth models by Myeongguen Shin, Juwon Jung, Jihyun Lee, Insoo Ryu, Sanggun Park

“… Software reliability is a critical factor for system performance and safety, especially in defense industries, where operational failures can have severe consequences. To evaluate and improve software reliability, Software Reliability Growth Models (SRGMs) are widely used. …”
Get full text

A Wi-Fi RSS-RTT Indoor Positioning Model Based on Dynamic Model Switching Algorithm by Xu Feng, Khuong An Nguyen, Zhiyuan Luo

“…However, their performance varies significantly across different indoor environments, making it challenging to identify the most suitable system for all scenarios. To address this challenge, we propose an algorithm that dynamically selects the most optimal Wi-Fi positioning model for each location. …”
Get full text

Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…Due to the complexity of the flotation process mechanism, which makes it difficult to meet the requirements of advanced process control, a system identification modeling method was adopted. To address the low fitting accuracy of traditional identification methods, a Whale Optimization Algorithm (WOA)-based Gated Recurrent Unit (GRU) system identification model (WOA-GRU) was proposed. …”
Get full text

Improvement teaching-learning-based optimization algorithm for solar cell parameter extraction in photovoltaic systems by H. Khaterchi, M. H. Moulahi, A. Jeridi, R. Ben Messaoud, A. Zaafouri

“…Goal. The work aims to improve the Teaching-Learning-Based Optimization (TLBO) algorithm to enhance the accuracy of parameter extraction in PV models. …”
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

Model updating method for detect and localize structural damage using generalized flexibility matrix and improved grey wolf optimizer algorithm (I-GWO) by Sina Sadraei, Majid Gholhaki, Omid Rezaifar

Subjects: Get full text

Improved Directional Mutation Moth–Flame Optimization Algorithm via Gene Modification for Automatic Reverse Parking Trajectory Optimization by Yan Chen, Yi Chen, Yang Guo, Longda Wang, Gang Liu

“…To address this, we propose an improved directional mutation moth–flame optimization algorithm with gene modification (IDMMFO-GM). …”
Get full text

Distributed photovoltaic reactive power control strategy based on improved multiobjective particle swarm algorithm by Hongli Liu, Li Hao, Li Ji, Shao Lei

“…When the algorithm is compared with three other algorithms, such as nondominated sorting genetic algorithm‐II, the results show that it reduces the network loss by about 25% and significantly improves the voltage fluctuation rate.…”
Get full text

Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm by Wenjing Zhang, Hongjing Yan, Lili Xiang, Linling Shao

“…Then, the sparrow search algorithm and firefly algorithm are combined to optimize the hyperparameter configuration, improving the predictive performance and global search ability of the model. …”
Get full text

Optimization of Railway Transportation Planning by Combining TST Model and Genetic Algorithm by Wei Cao, Fan Chen

“…The study proposes an integrated method that combines the Temporal-Spatial Tunnel (TST) model with the Genetic Algorithm (GA). The TST model describes railway transportation changes dynamically by integrating temporal and spatial dimensions. …”
Get full text

IMPROVEMENT OF EVOLUTIONARY STRUCTURAL OPTIMIZATION METHOD FOR 2-D MODEL by CHEN XiaoMing, LAI XiDe, TANG Jian, ZHU Li, ZHAO Xi

“…which the singular element appears in the optimum process and the result may be a partial optimum solution are two disadvantages when using the ESO method to optimize 2- D model. In this paper,two algorithms are proposed for solving these disadvantages. …”
Get full text

An Improved Soft Island Model of the Fish School Search Algorithm with Exponential Step Decay Using Cluster-Based Population Initialization by Liliya A. Demidova, Vladimir E. Zhuravlev

“…The development of new optimization algorithms or the improvement of existing ones enhances the efficiency of various fields of activity. …”
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

Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
Get full text

Improved Gradient-Based Optimizer for Modelling Thermal and Hydropower Plants by Ahmed M. Agwa, Yehya I. Mesalam, Mohamed H. Hassan, Mahmoud A. El-Dabah, Anas M. El-Sherif, Salah Kamel

“…In this research, a modified optimization algorithm called an improved gradient-based optimizer (IGBO) is deployed for the optimal extraction of TPP and HPP input-output parameters. …”
Get full text

Novel nonlinear wind power prediction based on improved iterative algorithm by Fu Zhen-yu, Lin Gui-quan, Tian Wei-da, Pan Zhi-hao, Zhang Wei-cong

“…To effectively improve the accuracy of wind power prediction and reduce the load on the power grid, a new nonlinear wind power prediction model based on an improved iterative learning algorithm was investigated. …”
Get full text

Optimization Strategies for Atari Game Environments: Integrating Snake Optimization Algorithm and Energy Valley Optimization in Reinforcement Learning Models by Sadeq Mohammed Kadhm Sarkhi, Hakan Koyuncu

“…One of the biggest problems in gaming AI is related to how we can optimize and adapt a deep reinforcement learning (DRL) model, especially when it is running inside complex, dynamic environments like “PacMan”. …”
Get full text