No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
Get full text

A State-of-the-Art Survey on Advanced Electromagnetic Design: A Machine-Learning Perspective by Masoud Salmani Arani, Reza Shahidi, Lihong Zhang

“…Research on electromagnetic (EM) components is essential to enabling the design and optimization of such devices as antennas and filters, leading to improved functionality, reduced costs, and enhanced overall performance. …”
Get full text

The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
Get full text

UAM Vertiport Network Design Considering Connectivity by Wentao Zhang, Taesung Hwang

“…To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. …”
Get full text

Modeling of Cloud-Edge Collaborated Electricity Market Considering Flexible Ramping Products Provided by VPPs by PENG Chaoyi, CHEN Wenzhe, XU Suyue, LI Jianshe, ZHOU Huafeng, GU Huijie, NIE Yongquan, SUN Haishun

“…The distributed optimization model is iteratively solved using the analytical target cascading (ATC) method, and heuristic constraints are introduced to improve the convergence of the algorithm. …”
Get full text

Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

Get full text

Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications by Peiqingfeng Wang, Shusheng Xu, Xuerong Shi, Jiaqing Zhu, Haichao Xiong, Huimin Wen

“…Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. …”
Get full text

Balancing line hardening, distributed generation and de-energization for wildfire risk mitigation with microgrid formation by Mengqi Yao, Shunbo Lei, Weimin Wu, Duncan S. Callaway

“…The objective is to balance the desire to enhance system resilience while minimizing the system upgrade cost against wildfires. An adopted column-and-constraint generation algorithm is developed to solve the model and obtain the optimal decisions. …”
Get full text

Microcontroller-Driven Battery Management in Hybrid Energy Systems: A Systematic Review of Applications, Control Strategies, and Emerging Trends by Ripfumelo Humphrey Malele, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…Tools like Maximum Power Point Tracking (MPPT) and Pulse Width Modulation (PWM) help improve efficiency, while microcontrollers like Arduino and TMS320F28379D balance cost and performance depending on the project. …”
Get full text

Porosity prediction of tight reservoir rock using well logging data and machine learning by Yawen He, Hongjun Zhang, Zhiyu Wu, Hongbo Zhang, Xin Zhang, Xiaojing Zhuo, Xiaoli Song, Sha Dai, Wei Dang

“…These models are further optimized with the particle swarm optimization (PSO) algorithm to enhance their predictive accuracy. …”
Get full text

Stackelberg Game Based on Trajectory Prediction for Lane Change in Mixed Traffic by Baichuan Shi, Li Zhai, Chang Liu

“…The method develops a utility function for human-driven vehicles incorporating driving styles and safety-comfort-efficiency factors, with a corresponding cost function for autonomous vehicles. An improved Stackelberg game model integrates trajectory prediction of human-driven vehicles, while a bi-level optimization algorithm combining model predictive control and genetic algorithms jointly optimizes acceleration sequences and lane-change timing. …”
Get full text

Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. …”
Get full text

Design of Dual-Channel Supply Chain Network Based on the Internet of Things Under Uncertainty by Hamed Nozari, Hossein Abdi, Agnieszka Szmelter-Jarosz, Seyyed Hesamoddin Motevalli

“…In this paper, a mathematical model of a dual-channel supply chain network (DCSCN) based on the Internet of Things (IoT) under uncertainty is presented, and its solution using algorithms based on artificial intelligence such as genetic algorithm (GA), particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and gray wolf optimizer (GWO). …”
Get full text

Model for selective vehicle problem considering mixed fleet with capacitated electric vehicles by Jiacheng Li, Masato Noto, Yang Zhang, Jia Guo

“…Subsequently, an adaptive large neighborhood search algorithm, improved on the basis of simulated annealing principles and local search algorithms, is proposed. …”
Get full text

Random PWM Technique Based Two-State Markov Chain for Permanent Magnet Synchronous Motor Control by Zhiqiang Wang, Xinyuan Liu, Xuefeng Jin, Guozheng Zhang, Zhichen Lin

“…Secondly, to address the problem of insufficient random performance in the traditional RPWM technique, an innovative optimization scheme is proposed, i.e., the introduction of a two-state Markov chain and, based on the immune algorithm for transition probability and random gain, the optimization of two key parameters. …”
Get full text

Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…This study presents an innovative framework combining Digital Twin technology with Deep Learning to enhance fault detection, optimize operations, and improve system resilience. …”
Get full text

SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

Get full text

Enhancing Engineering and Architectural Design Through Virtual Reality and Machine Learning Integration by Ali Shehadeh, Odey Alshboul

Get full text

Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…Specifically, the VAE-based approach reduces total travel costs by an average of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>8</mn><mo>%</mo></mrow></semantics></math></inline-formula> and improves customer priority satisfaction by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>95</mn><mo>%</mo></mrow></semantics></math></inline-formula> compared to traditional hyperheuristic methods. …”
Get full text

Interference Minimization in Beyond-Diagonal RIS-Assisted MIMO Interference Channels by Ignacio Santamaria, Mohammad Soleymani, Eduard Jorswieck, Jesus Gutierrez

“…In the first stage, the passive BD-RIS is designed to minimize the aggregate interference power at all receivers, a cost function called interference leakage (IL). To this end, we propose an optimization algorithm in the manifold of unitary matrices and a suboptimal but computationally efficient solution. …”
Get full text