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. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. …”
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Research on an Intelligent Design Method for the Geometric Structure of Three-Layer Hollow Fan Blades by Jialin Lei, Jiale Chao, Chuipin Kong, Xionghui Zhou

“…The geometric structure design of three-layer hollow fan blades is extremely complex, which is not only directly related to the blade quality and manufacturing cost but also has a significant impact on engine performance. …”
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Analysis of the impact of mobile robots on the efficiency of warehousing and transport processes in modern textile manufacturing by Karabegović Isak

“…AMRs leverage advanced technologies such as LiDAR sensors, SLAM algorithms, artificial intelligence, and IoT systems to navigate complex industrial environments autonomously, optimize routes, and execute tasks without direct human intervention. …”
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LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

“…Predictive maintenance is essential for ensuring the reliability of industrial equipment and minimizing maintenance costs. However, current predictive algorithms sometimes reach their limits in terms of accuracy, necessitating continuous improvement. …”
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Addressing the Return Visit Challenge in Autonomous Flying Ad Hoc Networks Linked to a Central Station by Ercan Erkalkan, Vedat Topuz, Ali Buldu

“…This paper presents different approaches to efficiently directing UAVs and explains how heuristic algorithms can enhance our understanding and improve current methods for task assignments.…”
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Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

“…The experimental results show that compared to the single skill model, this model can effectively shorten project duration, reduce human resource costs, and improve skill scores. For example, in a specific experimental dataset, when the project duration is limited to 200 h, the most suitable labor duration for the plan is 193.8 h, the human resource cost is 7493 yuan, and the skill score is improved by 268. …”
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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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Enhancing energy efficiency of industrial boiler application by the integration of ground-source heat pumps and photovoltaic-thermal solar water collectors by Praveen Barmavatu, Baburao Gaddala, Sharun Mendonca, Sonali Anant Deshmukh, Marco Rosales-Vera, Hussein Togun, Ramalinga Viswanathan Mangalaraja, Vineet Singh Sikarwar

“…Significant reductions were observed in annual heating loads and grid-purchased electricity compared to traditional systems. Optimization was achieved using a hybrid approach that combined Genetic Algorithms (GA) and machine learning (ML) techniques, which iteratively improved system design and operational strategies. …”
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Navigating Intelligence: A Survey of Google OR‐Tools and Machine Learning for Global Path Planning in Autonomous Vehicles by Alexandre Benoit, Pedram Asef

“…This problem is central to enhancing ROMIE's operational efficiency and competitiveness against human labor by optimizing cost and time. The primary aim of this research is to advance GPP by developing, evaluating, and improving a cost‐efficient software and web application. …”
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Enhanced Multi-Model Deep Learning for Rapid and Precise Diagnosis of Pulmonary Diseases Using Chest X-Ray Imaging by Rahul Kumar, Cheng-Tang Pan, Yi-Min Lin, Shiue Yow-Ling, Ting-Sheng Chung, Uyanahewa Gamage Shashini Janesha

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The Design, Creation, Implementation, and Study of a New Dataset Suitable for Non-Intrusive Load Monitoring by Carlos Rodriguez-Navarro, Francisco Portillo, Francisco G. Montoya, Alfredo Alcayde

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Adaptive dynamic programming-based multi-fault tolerant control of reconfigurable manipulator with input constraint by Zhenguo Zhang, Tianhao Ma, Yadan Zhao, Shuai Yu, Fan Zhou

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Advancing Spike Sorting Through Gradient‐Based Preprocessing and Nonlinear Reduction With Agglomerative Clustering by Mohammad Amin Lotfi, Fatemeh Zareayan Jahromy, Mohammad Reza Daliri

“…The feature extraction process is centered around capturing inherent variations in spike waveforms, assuming that strong signal correlations enable the extraction of optimal features. Finally, a density‐based clustering algorithm is employed for spike sorting. …”
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Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning by Binqiao Zhang, Changlin He

“…By allowing agents to share parts of their neural network, the proposed Parameter Sharing - twin-delay deep deterministic policy gradient algorithm improves the stability and efficiency of voltage regulation. …”
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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

“…The findings highlight the increasing adoption of deep learning, reinforcement learning, and digital twins for anomaly detection and process optimization. Additionally, AI-driven methods are improving sensor-based data acquisition and asset management, extending equipment lifecycles while reducing failures. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones by Shuo Wei, Houming Fan, Xiaoxue Ren, Xiaolong Diao

“…Compared to the genetic neighborhood search algorithm and the hybrid genetic algorithm, the improvement rates are 5.1% and 13.0%, respectively. …”
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