Optimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying Networks by Zeyu WANG, Fujian CHEN, Chengcheng MO

“…Subsequently, we design an improved particle swarm optimisation algorithm suitable for time-varying networks. …”
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A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools by Yanjun Shi, Chengjia Yu, Shiduo Ning

“…This paper focuses on the flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) and proposes an improved genetic algorithm with a two-stage neighborhood search (IGA-TNS) to minimize total weighted tardiness (TWT). …”
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Configurational Comparison of a Binary Logic Transmission Unit Applicable to Agricultural Tractor Hydro-Mechanical Continuously Variable Transmissions and Its Wet Clutch Optimizati... by Wenjie Li, Zhun Cheng, Mengchen Yang

“…The WOA improved the spread value in the GRNN algorithm, establishing a GRNN to predict the optimal range for wet clutch design values in BLT-U; the model validation showed an average correlation coefficient of 0.92 for speed curves and an average relative error of 5.58% for dynamic loads. …”
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Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

“…To address the challenges of slow convergence and local optima in traditional PV microgrid scheduling methods, this study introduced an improved multiple objective particle swarm optimization (IMOPSO) algorithm that integrates an adaptive inertia weight adjustment strategy based on optimal similarity and a multi-directional iterative Pareto solution archive update mechanism. …”
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Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent by Ruslan I. Abdulkadirov, Pavel A. Lyakhov, Valentina A. Baboshina, Nikolay N. Nagornov

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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Ultimately, the multi-strategy improved APO is employed to optimize the hyperparameters of the BiLSTM–KAN model, allowing for the superposition of each subsequence to yield the final prediction results. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD Combining Signal Features and Improved CNN by Yingyong Zou, Xingkui Zhang, Wenzhuo Zhao, Tao Liu

“…The article proposes a rolling bearing fault diagnosis based on optimized variational mode decomposition (VMD) combined with signal features and an improved convolutional neural network (CNN). The golden jackal optimization (GJO) algorithm is employed to optimize the key parameters of the VMD, enabling effective signal decomposition. …”
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Change-Point Estimation and Detection for Mixture of Linear Regression Models by Wenzhi Zhao, Tian Cheng, Zhiming Xia

“…This paper studies the estimation and detection problems in the mixture of linear regression models with change point. An improved Expectation–Maximization (EM) algorithm is devised specifically for multi-classified mixture data with change points. …”
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Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm. by Jaspreet Kaur, Anders Nygren, Edward J Vigmond

“…Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. …”
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Low pressure PEM electrolyzer system modeling with heat loss representation by Asmaa A. Ghany, Mohamed Mahmoud Samy

“…These systems function efficiently at reduced pressures, leading to lower cost of operation and improved safety. A mathematical model is developed for the PEM electrolyzer to enhance the prediction of the system's behavior and output parameters, accompanied by a brief description of the assumption to simplify the model. …”
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Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm by Xiaojie Zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li

“…This study proposes a hybrid CNN-LSTM-Attention model optimized with an improved Dung Beetle Optimization (IDBO) algorithm to enhance predictive performance. …”
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms by Dongmei Tan, Wenjie Li, Yu Tao, Baifeng Ji

“…To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. …”
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Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

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Numerical Modeling on the Damage Behavior of Concrete Subjected to Abrasive Waterjet Cutting by Xueqin Hu, Chao Chen, Gang Wang, Jenisha Singh

“…In this study, a numerical framework based on a coupled Smoothed Particle Hydrodynamics (SPH)–Finite Element Method (FEM) algorithm incorporating the Riedel–Hiermaier–Thoma (RHT) constitutive model is proposed to investigate the damage mechanism of concrete subjected to abrasive waterjet. …”
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Optimization model of electricity metering management based on MOPSO by Sheng Li, Xiaodan Zhou

“…The optimization model based on MOPSO algorithm can achieve both accuracy and economy in energy metering management.…”
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Predicting the Compressive Strength of High-Performance Concrete utilizing Radial Basis Function Model integrating with Metaheuristic Algorithms by LiWei Hu

“…At the end of this article, it is seen that the SCA algorithm can combined better with the RBF model and achieve favorable and more satisfactory results with more accuracy and fewer errors.…”
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Training State-of-the-Art Deep Learning Algorithms with Visible and Extended Near-Infrared Multispectral Images of Skin Lesions for the Improvement of Skin Cancer Diagnosis by Laura Rey-Barroso, Meritxell Vilaseca, Santiago Royo, Fernando Díaz-Doutón, Ilze Lihacova, Andrey Bondarenko, Francisco J. Burgos-Fernández

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Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling by Raman Kumar, Jasgurpreet Singh Chohan, Sandeep Singh, Shubham Sharma, Yadvinder Singh, S. Rajkumar

“…Despite numerous advantages, the limitations of this technique are poor surface finish, dimensional accuracy, and mechanical strength, which must be improved. The present study focuses on the implementation of the genetic algorithm and Taguchi techniques to achieve minimum dimensional variability of FDM parts especially for polymeric biocomposites. …”
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FOX-TSA hybrid algorithm: Advancing for superior predictive accuracy in tourism-driven multi-layer perceptron models by Sirwan A. Aula, Tarik A. Rashid

“…Results indicate that the hybrid FOX-TSA achieves superior predictive accuracy (94.64 %), faster convergence speed (reducing iterations by 25 %), and improved F1-score (94.63 %) on the test dataset. These findings underline the potential of the hybrid FOX-TSA algorithm to advance predictive modelling in the tourism sector and other domains requiring complex data handling.…”
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Development of weighted residual RNN model with hybrid heuristic algorithm for movement recognition framework in ambient assisted living by Mustufa Haider Abidi, Hisham Alkhalefah, Zeyad Almutairi

“…The weighted deep learning model and a hybrid heuristic algorithm are proposed to achieve this goal. …”
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