Strategic Power Flow-Stackelberg Dynamics for Minimizing Transmission Losses in Peer-to-Peer Trading by K. V. Biji Varghese, Dattatraya N. Gaonkar

“…Results from these tests are compared with existing energy trading systems, highlighting improvements in scalability, efficiency, and overall performance. …”
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Enhanced load frequency regulation in microgrids with renewable energy sources and electric vehicles by Imran Khan, Suheel Abdullah Malik, Amil Daraz, Baitullah Bareer

“…Simulation results show that the (I-P) cascaded PDN controller significantly outperforms existing controllers, such as PID, and PI-based models, by reducing frequency deviations, improving settling time, and minimizing overshoot and error indices. …”
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Investigation on Photovoltaic Array Modeling and the MPPT Control Method under Partial Shading Conditions by Jianbo Bai, Leihou Sun, Rupendra Kumar Pachauri, Guangqing Wang

“…Optimized particle swarm optimization (OPSO) is used to control the multipeak output model that can quickly and accurately track the global maximum power point (GMPP) of PV modules under PSCs. …”
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Research on multimodal social media information popularity prediction based on large language model by WANG Jie, WANG Zitong, PENG Yan, HAO Bowen

“…Finally, an improved direct preference optimization (DPO) algorithm IDPOP was developed by constructing preference data and adding a parameter-tuned penalty to the DPO loss function, resolving instability and non-convergence in RLHF and incorrect optimization in standard DPO for social media popularity prediction. …”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…An extensive array of preprocessing techniques is thoroughly examined in order to optimize the predictive models’ quality and performance. …”
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Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…Experimental results demonstrate that the proposed quantum model outperforms classical algorithmic models in handling higher complexity, achieving improved efficiency, reduced computation time, and superior predictive performance. …”
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AI-Assisted Design of Drain-Extended FinFET With Stepped Field Plate for Multi-Purpose Applications by Xiaoyun Huang, Hongyu Tang, Chenggang Xu, Yuxuan Zhu, Yan Pan, Dawei Gao, Yitao Ma, Kai Xu

“…This study introduces a novel DE-FinFET featuring a stepped field plate to improve overall performance of device. Moreover, within an AI-assisted design framework, predictive modeling and multi-objective optimization of the device are accomplished using Kolmogorov–Arnold Networks (KAN) and the Nondominated Sorting Genetic Algorithm (NSGA-III). …”
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Enhanced Detection of Leishmania Parasites in Microscopic Images Using Machine Learning Models by Michael Contreras-Ramírez, Jhonathan Sora-Cardenas, Claudia Colorado-Salamanca, Clemencia Ovalle-Bracho, Daniel R. Suárez

“…Machine learning models (ANN, SVM, and RF) optimized through Grid Search were applied for classification. …”
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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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Design of an intelligent optimization system for high-altitude photovoltaic power plant output power prediction and enhancement using GVSAO-CNN-BiGRU-Attention by Shuai Yuan, Hui Zhou, Kai Zhao

“…The attention mechanism focuses on key features, improving prediction accuracy, and GVSAO optimizes model parameters for superior performance. …”
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Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data by Md Jobair Bin Alam, Ashish Gunda, Asif Ahmed

“…The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. …”
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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

“…The proposed framework offers improved accuracy, precision, and computational efficiency compared to state-of-the-art models. …”
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Visual Classification of Music Style Transfer Based on PSO-BP Rating Prediction Model by Tianjiao Li

“…At the same time, we take advantage of the BP neural network’s ability to handle complex nonlinear problems and construct a rating prediction model between the user and item attribute features, referred to as the PSO-BP rating prediction model, by combining the features of global optimization of particle swarm optimization algorithm, and make further improvements based on the traditional collaborative filtering algorithm.…”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…The proposed model combines multiple DL models to improve overall performance by leveraging the strengths of different architectures, ensembles can enhance accuracy, robustness, and generalization. …”
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Prediction of hydrogen production in proton exchange membrane water electrolysis via neural networks by Muhammad Tawalbeh, Ibrahim Shomope, Amani Al-Othman, Hussam Alshraideh

“…The integration of artificial intelligence (AI) and machine learning (ML) appears to be effective in optimization within the energy sector. Hence, this work employs the artificial neural network (ANN) to develop a model that accurately predicts HPR in PEMWE setups. …”
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THEORETICAL AND METHODOLOGICAL PRINCIPLES OF APPLICATION OF AGENT-ORIENTED APPROACH TO MODELING PROCESSES OF LOCAL HROMADAS by Yevgen Kotukh, Maryna Riabokin

“…The article also outlines a multi-step algorithm for modeling decision-making and coordination processes within the decentralized budget structure. …”
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Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia by Munkhsuren Badrakh, Narantsetseg Tserendash, Erdenejargal Choindonjamts, Gáspár Albert

“…Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. …”
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A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data by Ovais A Jaffery, Lea Melki, Gregory Slabaugh, Wilson W Good, Caroline H Roney

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Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network by Xiaorong Li, Lijun Zhang, Dongchen Li, Dan Guo

“…The optimization of the model training process is finally completed, and the recommendation quality is improved. …”
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YOLOv8-POS: a lightweight model for coal-rock image recognition by Yanqin Zhao, Wenyu Wang

“…This reduces unnecessary computational overhead while preserving the integrity of critical feature information, thus significantly cutting down on the model’s parameters and computational demands. Additionally, an Overlapping Spatial Reduction Attention module is incorporated into the model’s architecture to optimize the fusion of spatial features, substantially improving the handling of complex scenarios. …”
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