A 3D Multipath Planning Method for Guided Vehicles Using Improved A∗ Algorithm Based on Multiple Avoidance Tactics and Terminal Attack Angles by Jun Huang, Pengfei Wu, Xiaobao Li, Yue Liu

“…Intelligent optimization algorithms have the characteristics of random multiple solutions, whereas Classical A∗ approaches show time consumption, insufficient smoothness, unsettable terminal attack direction, and collisions between multiple paths. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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Design of indoor positioning method jointly assisted by RIS and IMU by SUN Wei, DU Xin, SONG Qingyang, GUO Lei

“…Finally, the Levenberg-Marquardt algorithm was employed to solve the optimization problem and estimate the UE’s position. …”
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Optimizing ensemble learning for satellite-based multi-hazard monitoring and susceptibility assessment of landslides, land subsidence, floods, and wildfires by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Farman Ali, Biswajeet Pradhan, Soo-Mi Choi

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Heterogeneous Graph Neural-Network-Based Scheduling Optimization for Multi-Product and Variable-Batch Production in Flexible Job Shops by Yuxin Peng, Youlong Lyu, Jie Zhang, Ying Chu

“…Moreover, the Proximal Policy Optimization (PPO) algorithm is leveraged to achieve end-to-end optimization of scheduling decisions. …”
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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

“…Furthermore, this analysis highlights the importance of data quality and the integration of advanced technologies to deliver an intelligent route optimization system with significant reductions in cost and time. …”
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Optimization method of task uninstallation in mobile edge computing environment combining improved deep Q-learning and transmission learning by Lihong Zhao, Shuqin Wang, Xiaomei Ding

“…Abstract Traditional task uninstallation methods are difficult to cope with the continuous changes in network environment and device status, therefore a more intelligent solution is urgently needed. This article studied the optimization method of task uninstallation in mobile edge computing (MEC) environment, and studied the optimization method of task uninstallation in combination with improved deep Q-learning and transmission learning (TL). …”
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Neural Network Method of Controllers’ Parametric Optimization with Variable Structure and Semi-Permanent Integration Based on the Computation of Second-Order Sensitivity Functions... by Serhii Vladov, Lukasz Scislo, Nina Szczepanik-Ścisło, Anatoliy Sachenko, Victoria Vysotska

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Determination of disintegration time using formulation data for solid dosage oral formulations via advanced machine learning integrated optimizer models by Mohammed Ghazwani, Umme Hani

“…Abstract We evaluated the properties of tablets by artificial intelligence and machine learning computational approach with integration of optimizer. …”
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A Cooperative GNSS Vector-DLL (CoVDLL) Method for Multiple UAVs Positioning by Chuntao Li, Xinru Wang, Changhui Jiang, Zikang Su, Shoubin Chen, Yuwei Chen

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An effectiveness of deep learning with fox optimizer-based feature selection model for securing cyberattack detection in IoT environments by Mimouna Abdullah Alkhonaini

“…Deep learning (DL) is one of the main technologies of today’s smart cybersecurity policies or systems for functioning intelligently. This paper presents a Fox Optimizer-Based Feature Selection with Deep Learning for Securing Cyberattack Detection (FOFSDL-SCD) model. …”
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Dung beetle optimizer based on mean fitness distance balance and multi-strategy fusion for solving practical engineering problems by Wanru Tang, Haoze Qin, Shuang Kang

“…Abstract As a swarm intelligence algorithm, Dung beetle optimizer (DBO) was inspired by the behavior pattern of dung beetles for survival. …”
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Damage Diagnosis in 3D Structures Using a Novel Hybrid Multiobjective Optimization and FE Model Updating Framework by Nizar Faisal Alkayem, Maosen Cao, Minvydas Ragulskis

“…Within that area, the damage tracking in 3D structures is evaluated as a more complex and difficult task. Swarm intelligence and evolutionary algorithms (EAs) can be well adapted for solving the problem. …”
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Preference learning based deep reinforcement learning for flexible job shop scheduling problem by Xinning Liu, Li Han, Ling Kang, Jiannan Liu, Huadong Miao

“…To address this, this paper proposes a Preference-Based Mask-PPO (PBMP) algorithm, which leverages the strengths of preference learning and invalid action masking to optimize FJSP solutions. …”
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A Density Functional Theory-Based Particle Swarm Optimization Investigation of Metal Sulfide Phases for Ni-Based Catalysts by Houyu Zhu, Xiaohan Li, Xiaoxin Zhang, Yucheng Fan, Xin Wang, Dongyuan Liu, Zhennan Liu, Xiaoxiao Gong, Wenyue Guo, Hao Ren

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Prospects of cold plasma in enhancing food phenolics: analyzing nutritional potential and process optimization through RSM and AI techniques by M. Anjaly Shanker, Sandeep Singh Rana

“…Response surface methodology (RSM) is one of the common techniques involved in the optimization of these course factors. It also covers the convention of artificial intelligence-based methods, such as artificial neural networks (ANN) and genetic algorithms (GA), in evaluating the data on process parameters. …”
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Sensitivity Analysis for Dynamic Parameters of High–Speed Train Based on Multimodal–Optimization Improved Kriging Model and Distance Correlation by Jie JIANG, Xufeng YANG, Guofu DING

“…Contrasting with traditional single-objective intelligent optimization algorithms, the algorithm presented here transforms a single-objective optimization problem into a double-objective optimization problem by introducing the population-diversity index. …”
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A Review of Quantitative Characterization of Phase Interface Dynamics and Optimization of Heat Transfer Modeling in Direct Contact Heat Transfer by Mingjian Wang, Jianxin Xu, Shibo Wang, Hua Wang

“…Based on the findings above, three key directions are proposed to guide future research to inform the exploration of direct contact heat transfer mechanisms in future work: 1 dynamic analysis of multi-scale spatio-temporal coupling mechanisms, 2 accurate quantification of unsteady interfacial heat transfer processes, and 3 synergistic integration of intelligent optimization algorithms with experimental datasets.…”
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Adaptive Neuro-Fuzzy Inference System-Genetic Algorithm approach for global maximum power point tracking in PV systems under different shading conditions by Nivine Guler, Zied Ben Hazem, Ali Gunes, Firas Saidi

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