Taking the lag out of jet lag through model-based schedule design. by Dennis A Dean, Daniel B Forger, Elizabeth B Klerman

“…In this paper, the use of mathematical models to design sleep-wake and countermeasure schedules for improved performance is demonstrated. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Two stage-specific models were constructed, with the number of hidden layer neurons, dropout rate, and batch size determined by the optimal solutions obtained via GWO. …”
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NoiseAugmentNet-HHO: Enhancing Histopathological Image Classification Through Noise Augmentation by Prem Purusottam Jena, Debahuti Mishra, Kaberi Das, Sashikala Mishra

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Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

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Modeling vector control of the asynchronous drive of electric rolling stock auxiliary machines by Yu. M. Kulinich, S. A. Shukharev, V. K. Dukhovnikov, A. V. Gulyaev

“…The developed complex of an asynchronous motor and a vector control system enable to work out various algorithms for improving the energy efficiency of the operation of asynchronous auxiliary machines of an electric locomotive by applying the proposed algorithm for choosing the optimal value of the rotor flux linkage. …”
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Analysis of the state of geometrization development and digital modeling in open-pit mining enterprises by M.S. Kunytska, D.S. Polishchyk, O.V. Shapochnikov

“…The article is devoted to the study of modern technologies of geometrization and digital modeling at open-pit mining enterprises. The relevance of the work is due to the requirements for optimizing mining processes, ensuring labor safety and increasing economic efficiency in the exploitation of deposits. …”
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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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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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Multi-objective optimization of custom implant abutment design for enhanced bone remodeling in single-crown implants using 3D finite element analysis by Pongsakorn Poovarodom, Chaiy Rungsiyakull, Jarupol Suriyawanakul, Qing Li, Keiichi Sasaki, Nobuhiro Yoda, Pimduen Rungsiyakull

“…In conclusion, the depth and taper have a significant effect on bone remodeling. This optimized model significantly improves bone density uniformity.…”
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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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Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…This research highlights the potential of nature-inspired optimization algorithms and tailored datasets to enhance AI model robustness and adaptability in the context of medical disease diagnosis, particularly in the field of diabetic eye disease.…”
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Revealing the Driving Factors of Household Energy Consumption in High-Density Residential Areas of Beijing Based on Explainable Machine Learning by Zizhuo Qi, Lu Zhang, Xin Yang, Yanxia Zhao

“…Data were collected through field surveys, questionnaires, and interviews, covering 16 influencing factors across household, building, environment, and transportation categories. A hyperparameter-optimized ensemble model (XGBoost, RF, GBDT) was employed, with XGBoost combined with genetic algorithm tuning performing best. …”
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The Location Privacy Protection Technology of Mobile Intelligent Terminal by LI Zhi-peng, SUN Ming-song, SONG Zeng-lin

“…Based on the existing encryption and distortion algorithm models，it introduces a coordinate transformation method，increases fragmentation of user location information，and optimizes the technologies of dummies and false-name. …”
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Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

“…The Shapley Additive Explanation (SHAP) algorithm was employed to explain the optimal model, and the AUC was used to assess the model’s performance. …”
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Strategic Power Flow-Stackelberg Dynamics for Minimizing Transmission Losses in Peer-to-Peer Trading by K. V. Biji Varghese, Dattatraya N. Gaonkar

“…In networked microgrids, some units may have surplus energy while others experience deficits, creating a buyer-seller trade dynamic. This dynamic is modeled using a multi-leader, multi-follower Stackelberg game. …”
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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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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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Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization) by Almira Budiyanto, Keisuke Azetsu, Nobutomo Matsunaga

“…When transfer learning is combined with fast computation, the efficiency of edge-level re-learning is improved. This paper proposes a formation change algorithm that allows easy and fast multi-robot knowledge transfer using SDPA combined with MAPPO (Multi-Agent Proximal Policy Optimization), compared to other methods. …”
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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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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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