Showing 2,461 - 2,480 results of 4,960 for search '(intelligent OR intelligence) optimization algorithms', query time: 0.18s Refine Results
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    A Survey on UAV Control with Multi-Agent Reinforcement Learning by Chijioke C. Ekechi, Tarek Elfouly, Ali Alouani, Tamer Khattab

    Published 2025-07-01
    “…There is a growing demand for autonomous, scalable, and intelligent coordination strategies in complex aerial missions involving multiple Unmanned Aerial Vehicles (UAVs). …”
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    Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

    Published 2025-04-01
    “…However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. …”
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  5. 2465

    Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

    Published 2025-01-01
    “…This paper introduces the Heuristic Binary Search, an intelligent search algorithm that efficiently explores the solution space, accommodating arbitrary cost function constraints similar to Finite Control Set, while maintaining a fixed switching frequency. …”
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  6. 2466

    An AI-Based Framework for Characterizing the Atmospheric Fate of Air Pollutants Within Diverse Environmental Settings by Nataša Radić, Mirjana Perišić, Gordana Jovanović, Timea Bezdan, Svetlana Stanišić, Nenad Stanić, Andreja Stojić

    Published 2025-02-01
    “…This study introduces a novel artificial intelligence (AI) modeling framework that combines machine learning algorithms optimized through metaheuristics with explainable AI to capture complex interactions among pollutant concentrations, meteorological data, and socio-economic indicators. …”
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    Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

    Published 2023-01-01
    “…In addition to making healthcare more intelligent and individualized, machine learning has the potential to transform the conventional healthcare system. …”
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    Multi-objective allocation optimization model for water resources from a coal mine in the Inner Mongolia-Shaanxi contiguous area by Hechao MIAO, Shuning DONG, Hao WANG, Yuanyuan YANG, Wei QIAO, Xiaodong WANG, Dongqi WANG, Hongyang FU, Yuting LIU

    Published 2025-07-01
    “…Therefore, advancing intelligent mine water control technology is identified as a crucial method to address the conflicts between coal mining and mine water in the western region. …”
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    Video semantics-driven resource allocation algorithm in Internet of vehicles by Jiujiu CHEN, Chunyan FENG, Caili GUO, Yang YANG, Qizheng SUN, Meiyi ZHU

    Published 2021-07-01
    “…Aiming at the problem that traditional resource allocation methods will no longer be applicable, with the demand of intelligent computing services such as video semantic understanding in Internet of vehicles, the video semantic driven resource allocation algorithm was studied.First of all, taking the object detection task as an example, a semantic driven resource allocation guidance model for video was proposed and an algorithm for solving model parameters was given.Secondly, an optimization problem of resource allocation driven by video semantics in Internet of vehicles was constructed, which was transformed into a convex problem and solved by convex optimization algorithm.Furthermore, in order to reduce the complexity of the convex optimization algorithm, a resource allocation algorithm based on reinforcement Q learning was proposed.Finally, the performance advantages of the proposed algorithm are verified by simulations.…”
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