Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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A clustering-based multi-setting overcurrent protection approach with optimisation and experimental validation for distribution networks by Feras Alasali, Mohamed Salem, Haytham Y. Mustafa, Hassen Loukil, Naser El-Naily, Abdelaziz Salah Saidi, William Holderbaum

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Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source by P. Sundararaman, E. Mohan, S. V. Aswin Kumer, Sridhar Udayakumar, Abdissa Fekadu Moti

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Breast Cancer Classification with Various Optimized Deep Learning Methods by Mustafa Güler, Gamze Sart, Ömer Algorabi, Ayse Nur Adıguzel Tuylu, Yusuf Sait Türkan

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Estimating Tea Plant Physiological Parameters Using Unmanned Aerial Vehicle Imagery and Machine Learning Algorithms by Zhong-Han Zhuang, Hui-Ping Tsai, Chung-I Chen

“…Using feature ranking methods, an optimized dataset was developed, and the predictive performance of eight regression algorithms was assessed for estimating tea plant physiological parameters. …”
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Identifying representative sequences of protein families using submodular optimization by Ha Nguyen, Hung Nguyen, Phuong Nguyen, Anh N. Luu, David C. Cantu, Tin Nguyen

“…Abstract Identifying representative sequences for groups of functionally similar proteins and enzymes poses significant computational challenges. In this study, we applied submodular optimization, a method effective in data summarization, to select representative sequences for thioesterase enzyme families. …”
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A Theoretical Bound Which Improves the Performance of Compilation-Based Multi-Agent Path Finding by Rodrigo Lopez, Roberto Asin-Acha, Jorge A. Baier

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Optimizing Apache Spark MLlib: Predictive Performance of Large-Scale Models for Big Data Analytics by Leonidas Theodorakopoulos, Aristeidis Karras, George A. Krimpas

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A Multi-Objective Bio-Inspired Optimization for Voice Disorders Detection: A Comparative Study by Maria Habib, Victor Vicente-Palacios, Pablo García-Sánchez

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δ-perturbation of bilevel optimization problems: An error bound analysis by Margarita Antoniou, Ankur Sinha, Gregor Papa

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A Transfer Matrix Norm-Based Framework for Multimaterial Topology Optimization: Methodology and MATLAB Implementation by Giacomo Galuppini, Paolo Venini

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Convergence-Driven Adaptive Many-Objective Particle Swarm Optimization by Yunfei Yi, ZhiYong Wang, Yunying Shi, Zhengzhuo Song, Binbin Zhao

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Steepest-Descent Approach to Triple Hierarchical Constrained Optimization Problems by Lu-Chuan Ceng, Cheng-Wen Liao, Chin-Tzong Pang, Ching-Feng Wen

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Hybrid Deep Learning Techniques for Improved Anomaly Detection in IoT Environments by Hanan Abbas Mohammad

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Noise-augmented chaotic Ising machines for combinatorial optimization and sampling by Kyle Lee, Shuvro Chowdhury, Kerem Y. Camsari

“…This improves performance in combinatorial optimization, achieving algorithmic scaling comparable to probabilistic bits (p-bits). …”
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Program Complex for Calculation and Optimization of the Regimes of Electric Power Systems by O. I. Alexandrov, A. M. Bakanovsky, V. A. Ustimovich

“…The possibilities of modem computers have permitted to apply more advanced algorithms. …”
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A review on multi-fidelity hyperparameter optimization in machine learning by Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

“…However, hyperparameter optimization (HPO) often demands significant computational budget, which is typically limited. …”
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A Novel Graphical Technique for Combinational Logic Representation and Optimization by Vedhas Pandit, Björn Schuller

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Coordinated Optimal Control of Secondary Cooling and Final Electromagnetic Stirring for Continuous Casting Billets by Dongsheng Wu, Zhenping Ji, Jian Yang, Hongwei Gao, Jiahui Yu, Zhaojie Ju

“…In this paper, a coordinated optimal control strategy based on a multiobjective particle swarm optimization (MOPSO) algorithm is proposed for the parameter optimization of secondary cooling and F-EMS, which is solved based on multiobjective particle swarm optimization (MOPSO) algorithm. …”
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Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

“…However, using most of these software tools and choosing the most appropriate algorithm for a given optimization task require substantial technical expertise, which prevents the majority of researchers from using these methods effectively. …”
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