Effective deployment strategies for optimizing area coverage in multistatic sonar detection based on Cassini oval approximation and a virtual force algorithm by Liufang Fu, Ming Zhou, Linzhou Xu, Xiaoming Dong, Zhu Kou, Chunyu Kang

“…The area coverage of multistatic sonar is a multi-objective optimization problem (MOOP) balancing maximum coverage against minimal cost. …”
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Optimization of integrated energy system considering P2G oxygen-enriched improvement and hybrid solar energy utilization by Xiaohui YANG, Zhao WAN, Riying XIAO, Zeyu YANG, Zecheng HU, Chilyu WU

“…Secondly, because the boiler efficiency is affected by the oxygen concentration, the optimal oxygen supply state for each period of the oxygen-consuming equipment is determined by a combined algorithm of genetic algorithm and Gurobi solver. …”
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Three-dimensional design, simulation and optimization of a centrifugal compressor impeller with double-splitter blades by Mohammadjavad Tasharrofi, Mojtaba Heidarian Shahri, Ali Madadi

“…Since the optimization process only using genetic algorithms is very time-consuming and has high computational costs, artificial neural networks were used to reduce costs. …”
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Enhanced probabilistic prediction of pavement deterioration using Bayesian neural networks and cuckoo search optimization by Feng Xiao, Biying Shi, Jie Gao, Huapeng Chen, Di Yang

“…Therefore, this study proposed an improved probabilistic model for pavement deterioration prediction based on the coupling of Bayesian neural network (BNN) and cuckoo search (CS) algorithm. …”
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Framework for Personalizing Wearable Devices Using Real-Time Physiological Measures by Prakyath Kantharaju, Sai Siddarth Vakacherla, Michael Jacobson, Hyeongkeun Jeong, Meet Nikunj Mevada, Xingyuan Zhou, Matthew J. Major, Myunghee Kim

“…In this study, we present an open-source, device-independent personalization framework that allows for human-in-the-loop optimization. This modular framework includes cost functions and optimization algorithms that use a physiological response to optimize wearable robot parameters. …”
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Noise Processing Method of MEMS Tilt Sensor Using Improved Kalman Filter Based on Quantum Particle Swarm Optimization by Yutong Ge, Weizheng Ren, Kaile Yu, Yiran Zhang, Yuxiao Li

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Machine Learning Performance Analysis for Bagging System Improvement: Key Factors, Model Optimization, and Loss Reduction in the Fertilizer Industry by Ari Primantara, Udisubakti Ciptomulyono, Berlian Al Kindhi

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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…To address the issue of rolling bearing fault diagnosis, this paper proposes a novel model combining the Improved Gorilla Troop Optimization (IGTO) algorithm, Variational Mode Decomposition (VMD), Permutation Entropy (PE), and Long Short-Term Memory (LSTM) networks. …”
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A Robust Salp Swarm Algorithm for Photovoltaic Maximum Power Point Tracking Under Partial Shading Conditions by Boyan Huang, Kai Song, Shulin Jiang, Zhenqing Zhao, Zhiqiang Zhang, Cong Li, Jiawen Sun

“…Finally, the integration with P&O facilitates a meticulous search with a small step size, ensuring swift convergence and further mitigating post-convergence power oscillations. Both the simulations and the experimental results indicate that the proposed algorithm outperforms particle swarm optimization (PSO) and grey wolf optimization (GWO) in terms of convergence velocity, tracking precision, and the reduction in iteration power oscillation magnitude.…”
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Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm-Random Forest Regression by Muhammad Shahzad Nazir, Sami ud Din, Wahab Ali Shah, Majid Ali, Ali Yousaf Kharal, Ahmad N. Abdalla, Padmanaban Sanjeevikumar

“…The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). …”
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Techno-Economic Enhancement of Distribution Network by Optimal DG Allocation Along with Network Reconfiguration Considering Different Load Models and Levels by Chintan D. Patel, Tarun Kumar Tailor, Samyak S. Shah, Gulshan Sharma, Pitshou N. Bokoro

“…Therefore, this work focuses on improving DN performance with optimal DG integration along with NR. …”
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Minimization of Material Waste Through Maintenance Interval Optimization in Transport Systems by Augustyn Lorenc, Małgorzata Kuźnar

“…Although the case study is based on railway vehicles, the approach is applicable to road, maritime, and air transport as well. By leveraging optimization algorithms, such as machine learning, this solution predicts optimal maintenance timing, thereby reducing resource consumption and improving operational efficiency. …”
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Enhanced Multi-Threshold Otsu Algorithm for Corn Seedling Band Centerline Extraction in Straw Row Grouping by Yuanyuan Liu, Yuxin Du, Kaipeng Zhang, Hong Yan, Zhiguo Wu, Jiaxin Zhang, Xin Tong, Junhui Chen, Fuxuan Li, Mengqi Liu, Yueyong Wang, Jun Wang

“…The method avoids premature convergence and improves population diversity by embedding the crossover mechanism of Differential Evolution (DE) into the Whale Optimization Algorithm (WOA) and introducing a vector disturbance strategy. …”
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Adaptive hybrid optimization for integrated project scheduling and staffing problem with time/resource trade-offs by Muhai Hu, Yao Wang, Wendi Tian

“…To solve this problem, we introduce an adaptive hybrid algorithm combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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Demand side management with electric vehicles and optimal renewable resources integration under system uncertainties by Mohamed Mostafa Eissa, Rania Abdel Wahed Swief, Tarek Saad Abdel Salam

“…The study utilizes the Zebra optimization algorithm (ZOA), in comparison with the Whale optimization algorithm (WOA), Grey wolf optimization algorithm (GWO), and Genetic algorithm (GA). …”
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Three-Layer Energy Optimization Strategy for CHP Microgrid Considering Path Loss by Kai LING, Can WANG, Gaorui ZHANG, Aoqi WANG, Sihu CHU, Fuyin TIAN, Xinran LI

“…The middle layer model improves the energy mutual aid ability between microgrids through barter and trading transactions and searches for the optimal transmission path for energy transactions between microgrids based on the Floyd-Warshall algorithm. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Abstract Artificial intelligence has revolutionized various industries, including chemical process optimization. Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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Enhancing Route Optimization in Road Transport Systems Through Machine Learning: A Case Study of the Dakhla-Paris Corridor by Najib El Karkouri, Lahcen Hassine, Younes Ledmaoui, Hasna Chaibi, Rachid Saadane, Nourddine Enneya, Mohamed El Aroussi

“…However, these systems face numerous challenges, particularly regarding safety, cost, and route optimization, requiring innovative and practical solutions to improve their overall performance. …”
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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…The integration of Deep Reinforcement Learning (DRL) with Evolutionary Algorithms (EAs) represents a significant advancement in optimizing smart city energy operations, addressing the inherent uncertainties and dynamic conditions of urban environments. …”
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