CFD-APSO Co-Optimization for Enhanced Heat Dissipation in a <i>Camellia oleifera</i> Harvester Engine Compartment by Wenfu Tong, Kai Liao, Lefeng Zhou, Haifei Chen, Hong Luo, Jichao Liang

“…Based on these findings, the component arrangement was reconfigured to improve thermal performance. Subsequently, an “engine compartment cover parameters–temperature” correlation model was established, and the dimensional parameters of the engine compartment cover were optimized using the APSO algorithm. …”
Get full text

Customer Clustering and Marketing Optimization in Hospitality: A Hybrid Data Mining and Decision-Making Approach from an Emerging Economy by Maryam Deldadehasl, Houra Hajian Karahroodi, Pouya Haddadian Nekah

“…Using a hybrid approach that integrates data mining with multi-criteria decision-making techniques, this study aims to identify valuable customer segments and optimize marketing strategies. This research applies the K-means clustering algorithm to classify customers from a hotel in Iran based on RMD attributes. …”
Get full text

Timetable Design of Metro Train Based on RegenerativeBraking Energy Utilization by HE Deqiang, WANG Heliang, TAN Wenju, MIAO Jian

“…The multiple vehicles energy-saving optimization model wasbuilt based on the use of regenerative braking energy and the design of timetable. …”
Get full text

Research on 3D modeling of underground roadways in coal mines by LIAN Boxiang, MI Langtao, LI Shangjie, GUO Jiyao

“…The Delaunay Triangulation algorithm was adopted to construct an irregular triangular mesh model of the underground roadway, and multi-stage optimization was used to achieve fine 3D reconstruction, which was finally presented via a visualization platform. …”
Get full text

Nondestructive detection of rape leaf chlorophyll level based on Vis/NIR spectroscopy by YAO Jian-song, YANG Hai-qing, HE Yong

“…The procedure of shaping the predictive model was as follows: firstly, prediction equation of rape leaf chlorophyll level was created with uncertain parameters; secondly, a standard genetic algorithm (GA) was designed for parameter optimization. …”
Get full text

Introducing Iterative Model Calibration (IMC) v1.0: a generalizable framework for numerical model calibration with a CAESAR-Lisflood case study by C. Banerjee, K. Nguyen, C. Fookes, G. Hancock, T. Coulthard

“…This approach efficiently identifies the optimal set of parameters for a given numerical model through a strategy based on a Gaussian neighborhood algorithm. …”
Get full text

Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators by Qin Yan, Jinxin Wang, Tao Lin, Archie James Johnston

“…Simulation results show that the proposed model improves grid resilience, enhances economic benefits for both aggregators and users, and optimizes the system’s performance. …”
Get full text

A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
Get full text

Optimized Demand Forecasting for Bike-Sharing Stations Through Multi-Method Fusion and Gated Graph Convolutional Neural Networks by Hebin Guo, Kexin Li, Yutong Rou

Get full text

Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

“…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
Get full text

Progress and perspectives on genomic selection models for crop breeding by Dongfeng Zhang, Feng Yang, Jinlong Li, Zhongqiang Liu, Yanyun Han, Qiusi Zhang, Shouhui Pan, Xiangyu Zhao, Kaiyi Wang

“…A series of algorithms have been proposed to improve the prediction accuracy of genomic selection. …”
Get full text

Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty by Guangxiu Yu, Ping Zhou, Zhenzhong Zhao, Yiheng Liang, Weijun Wang

“…Then, wind and solar output, as well as loads, are treated as fuzzy variables based on fuzzy chance constraints, and uncertainty constraints are transformed using clear equivalence class processing to establish a bi-level optimization model that considers uncertainties. A differential evolution algorithm and CPLEX are used for solving the upper and lower levels, respectively. …”
Get full text

GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…GIS model integration involves combining diverse spatial algorithms&mdash;such as buffer analysis, network analysis, spatial regression, and machine learning models&mdash;to tackle multifaceted geographic challenges. …”
Get full text

Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

“…A deep vision-based recognition system, enhanced by an improved YOLOv5 algorithm and multi-feature fusion, was employed for real-time object detection and pose estimation. …”
Get full text

Optimizing Automatic Voltage Control Collaborative Responses in Chain-Structured Cascade Hydroelectric Power Plants Using Sensitivity Analysis by Li Zhang, Jie Yang, Jun Wang, Lening Wang, Haiming Niu, Xiaobing Liu, Simon X. Yang, Kun Yang

“…Subsequently, a regional-voltage-coordinated regulation model is developed using sensitivity analysis, followed by the establishment of a mathematical model, solution algorithm, and operational procedure for multi-station AVC-coordinated response optimization. …”
Get full text

Fault Diagnosis Method for Vacuum Contactor Based on Time-Frequency Graph Optimization Technique and ShuffleNetV2 by Haiying Li, Qinyang Wang, Jiancheng Song

“…Secondly, multi-resolution GST time-frequency graphs are generated to cover signal characteristics in all frequency bands by adjusting the GST Gaussian window width factor <i>λ</i>. The OTSU algorithm is then combined to crop the energy concentration area, and the size of these time-frequency graphs is optimized by 68.86%. …”
Get full text

A comparison study and multi-objective optimization of a DICI engine fueled with petroleum diesel and Fischer-Tropsch diesel by Panpan Cai, Zheng Jing, Chunhua Zhang, Bing Han, Gang Li, Wenlong Song

“…Subsequently, non-dominated sorting genetic algorithm (NSGA-II) is applied to realize multi-objective optimization of fuel economy and emissions. …”
Get full text

An artificial intelligence and machine learning-driven CFD simulation for optimizing thermal performance of blood-integrated ternary nano-fluid by Mohib Hussain, Du Lin, Hassan Waqas, Qasem M. Al-Mdallal

“…However, conventional methods for modelling and optimizing these frameworks frequently encounter challenges owing to their intricacy and the multitude of interconnected variables. …”
Get full text

Control of steering wheel idle jitter based on optimization of engine suspension system with verifications using multi-sensor measurement by Shuilong He, Binqiang Chen, Zhansi Jiang, Yanxue Wang, Fuyun Liu

“…A multi-sensor-based measurement strategy was utilized to evaluate the idle jitter severity of the steering wheel. In order to improve the indicators of the decoupling degree, the vibration transmissibility, and the resonant frequency distributions of the engine suspension system, an optimization model of engine suspension system was established. …”
Get full text

Risk-managed economic dispatch in hybrid hydrothermal-wind-solar systems: a novel multi-objective optimization approach by Zhe Wang, Tao Sun, Na Liu

“…A Multi-Objective Artificial Rabbits Optimization (MOARO) algorithm, incorporating Pareto criteria and fuzzy theory, is applied to optimize dispatch decisions while balancing cost and risk. …”
Get full text