Research on unmanned mining truck path planning based on grey wolf optimization adaptive hybrid A* and artificial potential field by HAN Yanling, LYU Jinke, ZHOU Guofeng, ZHANG Like, ZHANG Yun

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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”. …”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…This study focuses on exploring collaborative optimization strategies for a nonlinear control system of railway signals based on the BBO algorithm. Currently, the railway signal control system faces performance bottlenecks such as response lag and local optima due to parameter coupling when dealing with multi-objective optimization problems like train operating speed and signal delays. …”
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Multi-Objective Evolution and Swarm-Integrated Optimization of Manufacturing Processes in Simulation-Based Environments by Panagiotis D. Paraschos, Georgios Papadopoulos, Dimitrios E. Koulouriotis

“…More specifically, the concept of digital twin is applied to virtually replicate a physical system that leverages real-time data fusion from Internet of Things devices or sensors. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…To overcome these issues, the ISWO integrates dynamic adaptive grouping, perturbation dimension-symmetric distance optimization, and nonlinear time-varying weights, enhancing convergence speed and optimization accuracy. …”
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Highly Efficient JR Optimization Technique for Solving Prediction Problem of Soil Organic Carbon on Large Scale by Harsh Vazirani, Xiaofeng Wu, Anurag Srivastava, Debajyoti Dhar, Divyansh Pathak

“…Employing a combination of machine learning and deep learning techniques, we developed a novel data fusion approach that integrated Digital Elevation Model (DEM) data, MODIS satellite imagery, WOSIS soil profile data, and CHELSA environmental data. …”
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A TOPSIS based multi-objective optimal deployment of solar PV and BESS units in power distribution system electric vehicles load demand by Vinod Kumar Thunuguntla, Vijayasanthi Maineni, Satish Kumar Injeti, Polamarasetty P Kumar, Ramakrishna S S Nuvvula, C Dhanamjayulu, Mostafizur Rahaman, Baseem Khan

“…To improve the above metrics, optimal planning of inverter-based non-dispatchable PV units and dispatchable PV-BESS units in the distribution network by the inclusion of PHEVs electric load demand is addressed. …”
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A novel spectral transformation technique based on special functions for improved chest X-ray image classification. by Abeer Aljohani

“…The procedure is applied to a latest data set of X-Ray images. The data set is composed of X-Ray images of three different classes of patients, normal, Covid infected and pneumonia. …”
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Multiple Machine Learning as a Powerful Tool for Star Cluster Analysis by Denilso Camargo

“…In addition, a KNN smoothing algorithm is implemented to enhance the visualization of features like overdensities in the 5D space and intrinsic stellar sequences on the color–magnitude diagrams. …”
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Market Regime Identification and Variable Annuity Pricing: Analysis of COVID-19-Induced Regime Shifts in the Indian Stock Market by Mohammad Sarfraz, Guglielmo D’Amico, Dharmaraja Selvamuthu

“…This research contributes to the understanding of variable annuity pricing under regime-dependent dynamics in emerging markets and offers practical implications for improved risk management and policy formulation.…”
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Using machine learning and single nucleotide polymorphisms for improving rheumatoid arthritis risk Prediction in postmenopausal women. by Yingke Xu, Qing Wu

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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…This limited occurrence of suspected data strongly indicates that the dataset employed in this study is robust, ensuring a high degree of reliability in the model predictions. …”
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Visceral obesity anthropometric indicators as predictors of acute pancreatitis severity by Kaier Gu, Wenxuan Shang, Dingzhou Wang

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How can selection of biologically inspired features improve the performance of a robust object recognition model? by Masoud Ghodrati, Seyed-Mahdi Khaligh-Razavi, Reza Ebrahimpour, Karim Rajaei, Mohammad Pooyan

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A Lightweight, Intelligent Autonomous Exploration System for Indoor Robots Using Improved Random Walk With Back-Off Strategies by Blesson Mathews Luke, S. Abraham Sampson

“…Autonomous exploration in unstructured indoor settings requires effective navigation approaches to manage obstacles, dead ends, and resource constraints. Conventional algorithms, like the TurtleBot3 Drive (TB3), frequently struggle with inadequate area coverage, inefficient obstacle management, and substantial computational demands. …”
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Improving ICESat-2 photon classification and tree height estimation using Moran's I and machine learning by Mei-Kuei Lu, Sorin Popescu, Lonesome Malambo

“…Canopy heights derived from different models were validated against Airborne Laser Scanning (ALS) data. …”
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Performance Optimization and Comprehensive Analysis of Binary Nutcracker Optimization Algorithm: A Case Study of Feature Selection and Merkle–Hellman Knapsack Cryptosystem by Mohamed Abdel-Basset, Reda Mohamed, Ibrahim M. Hezam, Karam M. Sallam

“…Because of the continuous nature of the classical NOA and the discrete nature of the binary problems, two different families of transfer functions, namely S-shaped and V-shaped, are extensively investigated for converting the classical NOA into a binary variant, namely BNOA, applicable for various binary problems. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

“…Fractional‐Order Proportional‐Integral with Tilt Integral Double Derivative and Filter (FOPI‐TIDDN), a novel cascade controller optimized using the crow search (CS) algorithm, is proposed in this paper to overcome these issues. …”
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an-QNA: An Adaptive Nesterov Quasi-Newton Acceleration-Optimized CMOS LNA for 65 nm Automotive Radar Applications by Unal Aras, Lee Sun Woo, Tahesin Samira Delwar, Abrar Siddique, Anindya Jana, Yangwon Lee, Jee-Youl Ryu

“…It is also noted that the optimized LNA achieves a measured gain of 12.9 dB and an NF of 4.98 dB, and the IP₁dB is −17.8 dB. …”
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Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms by Yuyan Annie Pan, Fuliang Li, Anran Li, Zhiqiang Niu, Zhen Liu

“…This manuscript introduces a novel framework, the Physics-Guided Spatio-Temporal Graph Neural Network (PG-STGNN), specifically designed for traffic flow prediction. By integrating the principles of traffic flow physics with advanced spatio-temporal graph neural network algorithms, the framework captures complex spatio-temporal dependencies in traffic networks. …”
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