New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

“…Smooth path planning is crucial for mobile robots to ensure stable and efficient navigation, as it minimizes jerky movements and enhances overall performance Achieving this requires smooth collision-free paths. Partial Swarm Optimization (PSO) and Potential Field (PF) are notable path-planning techniques, however, they may struggle to produce smooth paths due to their inherent algorithms, potentially leading to suboptimal robot motion and increased energy consumption. …”
Get full text

Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…The ant colony optimization method identified the most relevant feature subsets using a clinical dataset, reducing model complexity while preserving predictive accuracy. …”
Get full text

Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…Feature fusion and dimensionality reduction using Uniform Manifold Approximation and Projection (UMAP) facilitate clustering, while Particle Swarm Optimization (PSO) determines the optimal number of clusters for efficient backlog prioritization. …”
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

“…This study addresses the optimization of the Vehicle Routing Problem (VRP) with prioritized customers by introducing and comparing two advanced solution approaches: a metaheuristic-based hyperheuristic framework and a Variational Autoencoder (VAE)-based hyperheuristic. …”
Get full text

A machine learning approach to assess the climate change impacts on single and dual-axis tracking photovoltaic systems by Udit Mamodiya, Indra Kishor, Priyam Ganguly, Isha Mukherjee, Nithesh Naik

“…COMLAT’s reinforcement learning controller optimized tracking angles with sub-second latency while minimizing mechanical movement. …”
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

Unmanned aerial vehicle path planning with hybrid motion algorithm for obstacle avoidance by Venkatasivarambabu Pamarthi, Richa Agrawal

“…To enhance trajectory optimization, the optimized motion planner enhances the Rapidly-exploring Random Tree (RRTX) method with a Covariant Hamiltonian Optimization for Motion Planning (CHOMP) algorithm-based optimizer. …”
Get full text

Estimation and Reduction of CO₂ Emissions From Fossil Fuel Power Plants in Bangladesh by Deepak Kumar Chowdhury, Nur Mohammad, Tanjim Mahmud, Md. Khaliluzzaman, Karl Andersson, Mohammad Shahadat Hossain

“…The paper presents Matpower Interior Point Solver (MIPS), and Dynamic Non-Linear Particle Swarm Optimization (DNPSO) algorithms to solve combined economic emission dispatch (CEED) to optimize generation dispatch and minimize emissions. …”
Get full text

Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Abstract This narrative review presents a comprehensive and state-of-the-art synthesis of how machine learning (ML) is transforming public health through enhanced prediction, personalized treatment, real-time surveillance, and intelligent resource optimization. Drawing from 170 peer-reviewed studies published up to 2024/2025, this work uniquely integrates cross-domain insights spanning disease outbreak forecasting, genomic data analysis, personalized medicine, mental health monitoring, and public health infrastructure planning. …”
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

Dance Motion Capture Based on Data Fusion Algorithm and Wearable Sensor Network by Yueru Li

“…The algorithm is an iterative optimization algorithm that divides each iteration into an expectation step and a great likelihood step, and the best convergence value can be found efficiently according to each iteration step. …”
Get full text

A Self-Learning Hyper-Heuristic Algorithm Based on a Genetic Algorithm: A Case Study on Prefabricated Modular Cabin Unit Logistics Scheduling in a Cruise Ship Manufacturer by Jinghua Li, Ruipu Dong, Xiaoyuan Wu, Wenhao Huang, Pengfei Lin

“…The GA-SLHH employs a genetic algorithm combined with a self-learning strategy as its high-level strategy (HLS), optimizing low-level heuristics (LLHs) while uncovering potential relationships between adjacent decision-making stages. …”
Get full text

Leveraging the Louvain algorithm for enhanced group formation and collaboration in online learning environments by Minkyung Lee, Priya Sharma

“…Abstract This study explores the dynamics of student interaction networks within an online asynchronous discussion forum, focusing on both whole group discussions and subgroup interactions distinguished by the Louvain algorithm, a renowned community detection method. …”
Get full text

Research on APF-Dijkstra Path Planning Fusion Algorithm Based on Steering Model and Volume Constraints by Xizheng Wang, Gang Li, Zijian Bian

“…First, perform an expansion treatment on the obstacles in the map, optimize the search direction of the Dijkstra algorithm and its planned global path, ensuring that the distance between the path and the expanded grid is no less than 1 m, and use the path points as temporary target points for the APF algorithm. …”
Get full text

An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Instead, it performs dimensionality reduction on input features through adaptive average pooling and utilizes the state update mechanism of the SSM module to significantly enhance feature representation and optimize information flow. Second, to address the limitations of SSM models in local feature modeling, this study incorporates the ConvNeXtV2 module to optimize the backbone network, improving the model’s ability to capture fine-grained local details and thereby strengthening its overall representation capability. …”
Get full text

An Adaptive View Selection Algorithm for Large-scale Cone-Beam CT Reconstruction by Jingsong Lin, Singanallur Venkatakrishnan, Obaidullah Rahman, Gregery T. Buzzard, Amirkoushyar Ziabari, Charles A. Bouman

“…In this paper, we propose an algorithm to optimize the scanning process by using geometric information about the object to be scanned. …”
Get full text

A Constrained Solution Update Strategy for Multiobjective Evolutionary Algorithm Based on Decomposition by Yuchao Su, Qiuzhen Lin, Jia Wang, Jianqiang Li, Jianyong Chen, Zhong Ming

“…This paper proposes a constrained solution update strategy for multiobjective evolutionary algorithm based on decomposition, in which each agent aims to optimize one decomposed subproblem. …”
Get full text

LEO multi-service routing algorithm based on multi-objective decision making by Li YANG, Jing SUN, Cheng-sheng PAN, Qi-jie ZOU

“…In low earth orbit(LEO) satellite networks,in view of the unbalanced link resource,it's difficult to meet differentiated quality of service(QoS) requirements and easily lead to reduce the efficiency of the whole network.A routing algorithm based on multi-objective decision making was proposed which defined LEO satellite network transmission service as the delay sensitive,sensitive bandwidth and reliability sensitive three categories.It used the eigenvector method to calculate service weights,and used the consistency ratio to determine whether it can be accepted.Based on the multi-objective decision making theory,it combined with the actual state of satellite network nodes and links and the specific requirements of the business,calculating the path that meets the QoS requirements of the service,so as to realize the LEO satellite network multi objective dynamic routing optimization.Established simulation platform based on the iridium network system simulated network delay,the uncertain characteristics like the residual bandwidth and packet error rate,route planning for the randomly generated three classes of business.The simulation results show that,the algorithm not only satisfies the QoS constrain while balancing the traffic load of the satellite link effectively,but also improves the performance on the throughput.…”
Get full text

Multi-AGV multitask collaborative scheduling based on an improved ant colony algorithm by Yazhen Zhu, Qing Song, Meng Li

“…Existing research mainly focuses on the optimization of automated guided vehicle (AGV) path planning and scheduling, emphasizing on the minimization of conflicts and deadlocks, multi-objective task scheduling, and metaheuristic algorithm optimization, while ignoring path stability and real-time path planning in dynamic environments. …”
Get full text

Detecting Planting Holes Using Improved YOLO-PH Algorithm with UAV Images by Kaiyuan Long, Shibo Li, Jiangping Long, Hui Lin, Yang Yin

“…Furthermore, the ATSS label allocation method is employed to optimize sample allocation and enhance detection effectiveness. …”
Get full text