Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…Traditional heuristic algorithms are limited in scalability and struggle to address the increasingly complex optimization problems of DNP. …”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Two novel architectures, Sparse Convolutional DenseNet201 with Self-Attention (SC-DSAN) and CNN-GRU, are fused at the network level using a depth concatenation layer, avoiding the computational costs of feature-level fusion. Bayesian Optimization (BO) is employed for dynamic hyperparameter tuning, and an Entropy-controlled Marine Predators Algorithm (EMPA) selects optimal features. …”
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Yield Diagnosis and Tuning for Emerging Semiconductors During Research Stage by Chunshan Wang, Zizhao Ma, Yuxuan Zhu, Chensheng Jin, Dongyu Chen, Chuxin Zhang, Yining Chen, Wenzhong Bao, Yufeng Xie

“…The process of taking a new semiconductor device from the lab to the factory involves a lot of time, funds and manpower, a large portion of which is spent on device yield improvement. In recent years new methods have been tried to rapidly improve yields and using machine learning (ML) algorithms is one option. …”
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Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning by Liangcai Zhou, Long Huo, Linlin Liu, Hao Xu, Rui Chen, Xin Chen

“…A heterogeneous multi-agent proximal policy optimization (H-MAPPO) DRL algorithm is introduced for multi-area power systems. …”
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Chamber shape optimization for ultra-high-pressure water-jet nozzle based on computational fluid dynamics method and a data-driven surrogate model by Wen-Tao Zhao, Zheng-Shou Chen, Yuan-Jie Chen, Jiang-Long Li

“…Firstly, to ensure optimization accuracy, an improved whale optimization algorithm (IWOA) was developed. …”
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Leveraging RRT^*: Probabilistically Interpreted Mechanisms Enhanced With P-HOPE and FLEX-OPT for Complex Path Planning by Yujie Miao, Haiyang Liu, Ziqiang Zhang, Yanju Liang

“…Second, a flexible mechanism FLEX-OPT is developed to adaptively and dynamically adjust the search strategy through real-time feedback and monitoring of the cost function to tackle the above-mentioned local minima problem, which significantly improves the convergence speed and path quality of the algorithm. …”
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A Particle Swarm Optimization-Based Ensemble Broad Learning System for Intelligent Fault Diagnosis in Safety-Critical Energy Systems with High-Dimensional Small Samples by Jiasheng Yan, Yang Sui, Tao Dai

“…In order to reduce the computational cost of the EBLS, which is constrained by the selection of its hyperparameters, the PSO algorithm is employed to optimize the hyperparameters of the EBLS. …”
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An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…In conducting multi-objective optimization for both the airfoil and serration shapes, the study demonstrates notable improvements: a 5 to 7% enhancement in aerodynamic performance alongside a simultaneous 1-4% reduction in noise compared to benchmark airfoils. …”
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Empowering Fuel Cell Electric Vehicles Towards Sustainable Transportation: An Analytical Assessment, Emerging Energy Management, Key Issues, and Future Research Opportunities by Tuhibur Rahman, Md. Sazal Miah, Tahia F. Karim, Molla Shahadat Hossain Lipu, Abu M. Fuad, Zia Ul Islam, M. M. Naushad Ali, Mohammed Nazmus Shakib, Shafrida Sahrani, Mahidur R. Sarker

“…To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. …”
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An enhanced approach for automatic annotation of error codes based on Seq2edit by Jian Wang, Tao Lin, Rongsen Zhao, Huiling Zhao

“…By dividing the code into statements with independent meanings and introducing a cost coefficient to improve the Levenshtein algorithm, this method optimizes the calculation of edit distance and enhances the ability to align tokens. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…Case studies conducted in Tunisia validate the system’s performance, showing a 20% reduction in energy costs and significant improvements in transaction efficiency. …”
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Prototype Mobile Vision System for Automatic Length Estimation of Olive Flounder (<i>Paralichthys olivaceus</i>) in Indoor Aquaculture by Inyeong Kwon, Hang Thi Phuong Nguyen, Paththige Waruni Prasadini Fernando, Hieyong Jeong, Sungju Jung, Taeho Kim

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Comparative analysis of lumped and semi-distributed hydrological models for an upland watershed in Ethiopia by Gebiaw T. Ayele, Bofu Yu

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Optimal Sizing, Techno-Economic Feasibility and Reliability Analysis of Hybrid Renewable Energy System: A Systematic Review of Energy Storage Systems&#x2019; Integration by Akhlaque Ahmad Khan, Ahmad Faiz Minai, Rakesh Kumar Godi, Vijay Shankar Sharma, Hasmat Malik, Asyraf Afthanorhan

“…The findings show that integrating HRES with ESS can lead to more sustainable energy systems, providing a long-term, reliable, and cost-effective solution. Findings emphasize the need for further study of optimization methods, meta-heuristic algorithm strategies, system components, design constraints, and desired techniques.…”
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Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Accurate prediction of electricity price (EP) is crucial for energy utilities and grid operators for enhancing the energy trading, grid stability studies, resource allocations and pricing strategies, thereby improving the overall grid reliability, efficiency, and cost-effectiveness. …”
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A Miniaturized and Intelligent Lensless Holographic Imaging System With Auto-Focusing and Deep Learning-Based Object Detection for Label-Free Cell Classification by Jin Chen, Wentao Han, Liangzun Fu, Zhihang Lv, Haotian Chen, Wenjing Fang, Jiale Hou, Haohan Yu, Xiwei Huang, Lingling Sun

“…Our system uses unstained cells suspended in solution as samples and employs a threshold segmentation-based auto-focusing algorithm to determine the optimal focusing distance for each imaging session. …”
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A Robust Adaptive Strategy for Diesel Particulate Filter Health Monitoring Using Soot Sensor Data by Bilal Youssef

“…Different cost functions have been tested and evaluated to improve the diagnostic performance. …”
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Torsional Vibration Characterization of Hybrid Power Systems via Disturbance Observer and Partitioned Learning by Tao Zheng, Hui Xie, Boqiang Liang

“…In contrast, incorporating the parameter self-learning algorithm reduces the RMSE to 2.36 N·m, representing an 85.2% improvement in estimation accuracy. …”
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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…Compared with the traditional parameter optimization approach, this paper uses the immune genetic algorithm to find the optimal hyperparameters of the model, which on the one hand has a wider choice of parameters, and on the other hand has been improved for the genetic algorithm is easy to fall into the local optimal solution, so as to improve the SOC estimation accuracy of the GRU model. …”
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