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  • Open Access

    ARTICLE

    Real-Time Implementation of Quadrotor UAV Control System Based on a Deep Reinforcement Learning Approach

    Taha Yacine Trad1,*, Kheireddine Choutri1, Mohand Lagha1, Souham Meshoul2, Fouad Khenfri3, Raouf Fareh4, Hadil Shaiba5

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4757-4786, 2024, DOI:10.32604/cmc.2024.055634 - 19 December 2024

    Abstract The popularity of quadrotor Unmanned Aerial Vehicles (UAVs) stems from their simple propulsion systems and structural design. However, their complex and nonlinear dynamic behavior presents a significant challenge for control, necessitating sophisticated algorithms to ensure stability and accuracy in flight. Various strategies have been explored by researchers and control engineers, with learning-based methods like reinforcement learning, deep learning, and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control systems. This paper investigates a Reinforcement Learning (RL) approach for both high and low-level quadrotor control systems, focusing on attitude stabilization and position… More >

  • Open Access

    ARTICLE

    An Optimisation Strategy for Electric Vehicle Charging Station Layout Incorporating Mini Batch K-Means and Simulated Annealing Algorithms

    Haojie Yang, Xiang Wen, Peng Geng*

    Journal on Artificial Intelligence, Vol.6, pp. 283-300, 2024, DOI:10.32604/jai.2024.056303 - 18 October 2024

    Abstract To enhance the rationality of the layout of electric vehicle charging stations, meet the actual needs of users, and optimise the service range and coverage efficiency of charging stations, this paper proposes an optimisation strategy for the layout of electric vehicle charging stations that integrates Mini Batch K-Means and simulated annealing algorithms. By constructing a circle-like service area model with the charging station as the centre and a certain distance as the radius, the maximum coverage of electric vehicle charging stations in the region and the influence of different regional environments on charging demand are… More >

  • Open Access

    ARTICLE

    A Strengthened Dominance Relation NSGA-III Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

    Liang Zeng1,2, Junyang Shi1, Yanyan Li1, Shanshan Wang1,2,*, Weigang Li3

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803 - 30 January 2024

    Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III… More >

  • Open Access

    ARTICLE

    Models to Simulate Effective Coverage of Fire Station Based on Real-Time Travel Times

    Sicheng Zhu, Dingli Liu*, Weijun Liu, Ying Li, Tian Zhou

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 483-513, 2024, DOI:10.32604/cmes.2023.044809 - 30 December 2023

    Abstract In recent years, frequent fire disasters have led to enormous damage in China. Effective firefighting rescues can minimize the losses caused by fires. During the rescue processes, the travel time of fire trucks can be severely affected by traffic conditions, changing the effective coverage of fire stations. However, it is still challenging to determine the effective coverage of fire stations considering dynamic traffic conditions. This paper addresses this issue by combining the traveling time calculation model with the effective coverage simulation model. In addition, it proposes a new index of total effective coverage area (TECA)… More >

  • Open Access

    ARTICLE

    Experimental Study on the Performance of ORC System Based on Ultra-Low Temperature Heat Sources

    Tianyu Zhou1, Liang Hao1, Xin Xu2,3, Meng Si2,3, Lian Zhang2,3,*

    Energy Engineering, Vol.121, No.1, pp. 145-168, 2024, DOI:10.32604/ee.2023.042798 - 27 December 2023

    Abstract This paper discussed the experimental results of the performance of an organic Rankine cycle (ORC) system with an ultra-low temperature heat source. The low boiling point working medium R134a was adopted in the system. The simulated heat source temperature (SHST) in this work was set from 39.51°C to 48.60°C by the simulated heat source module. The influence of load percentage of simulated heat source (LPSHS) between 50% and 70%, the rotary valve opening (RVO) between 20% and 100%, the resistive load between 36 Ω and 180 Ω or the no-load of the generator, as well… More >

  • Open Access

    ARTICLE

    Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

    Caixia Tao, Shize Yang*, Taiguo Li

    Energy Engineering, Vol.121, No.1, pp. 187-201, 2024, DOI:10.32604/ee.2023.042421 - 27 December 2023

    Abstract With the current integration of distributed energy resources into the grid, the structure of distribution networks is becoming more complex. This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms. Consequently, traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima. To tackle this issue, a more advanced particle swarm optimization algorithm is proposed. To address the varying emphases at different stages of the optimization process, a dynamic strategy is implemented to regulate the social and self-learning factors. The Metropolis criterion is introduced into… More >

  • Open Access

    ARTICLE

    An Improved Multi-Objective Hybrid Genetic-Simulated Annealing Algorithm for AGV Scheduling under Composite Operation Mode

    Jiamin Xiang1, Ying Zhang1, Xiaohua Cao1,*, Zhigang Zhou2

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3443-3466, 2023, DOI:10.32604/cmc.2023.045120 - 26 December 2023

    Abstract This paper presents an improved hybrid algorithm and a multi-objective model to tackle the scheduling problem of multiple Automated Guided Vehicles (AGVs) under the composite operation mode. The multi-objective model aims to minimize the maximum completion time, the total distance covered by AGVs, and the distance traveled while empty-loaded. The improved hybrid algorithm combines the improved genetic algorithm (GA) and the simulated annealing algorithm (SA) to strengthen the local search ability of the algorithm and improve the stability of the calculation results. Based on the characteristics of the composite operation mode, the authors introduce the… More >

  • Open Access

    ARTICLE

    Optimization of Cognitive Radio System Using Enhanced Firefly Algorithm

    Nitin Mittal1, Rohit Salgotra2,3, Abhishek Sharma4, Sandeep Kaur5, S. S. Askar6, Mohamed Abouhawwash7,8,*

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 3159-3177, 2023, DOI:10.32604/iasc.2023.041059 - 11 September 2023

    Abstract The optimization of cognitive radio (CR) system using an enhanced firefly algorithm (EFA) is presented in this work. The Firefly algorithm (FA) is a nature-inspired algorithm based on the unique light-flashing behavior of fireflies. It has already proved its competence in various optimization problems, but it suffers from slow convergence issues. To improve the convergence performance of FA, a new variant named EFA is proposed. The effectiveness of EFA as a good optimizer is demonstrated by optimizing benchmark functions, and simulation results show its superior performance compared to biogeography-based optimization (BBO), bat algorithm, artificial bee More >

  • Open Access

    ARTICLE

    Research on Optimization of Dual-Resource Batch Scheduling in Flexible Job Shop

    Qinhui Liu, Zhijie Gao, Jiang Li*, Shuo Li, Laizheng Zhu

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2503-2530, 2023, DOI:10.32604/cmc.2023.040505 - 30 August 2023

    Abstract With the rapid development of intelligent manufacturing and the changes in market demand, the current manufacturing industry presents the characteristics of multi-varieties, small batches, customization, and a short production cycle, with the whole production process having certain flexibility. In this paper, a mathematical model is established with the minimum production cycle as the optimization objective for the dual-resource batch scheduling of the flexible job shop, and an improved nested optimization algorithm is designed to solve the problem. The outer layer batch optimization problem is solved by the improved simulated annealing algorithm. The inner double resource More >

  • Open Access

    ARTICLE

    Numerical Approach to Simulate the Effect of Corrosion Damage on the Natural Frequency of Reinforced Concrete Structures

    Amthal Hakim1, Wael Slika1,*, Rawan Machmouchi1, Adel Elkordi2

    Structural Durability & Health Monitoring, Vol.17, No.3, pp. 175-194, 2023, DOI:10.32604/sdhm.2022.023027 - 25 June 2023

    Abstract Corrosion of reinforcing steel in concrete elements causes minor to major damage in different aspects. It may lead to spalling of concrete cover, reduction of section’s capacity and can alter the dynamic properties. For the dynamic properties, natural frequency is to be a reliable indicator of structural integrity that can be utilized in non-destructive corrosion assessment. Although the correlation between natural frequency and corrosion damage has been reflected in different experimental programs, few attempts have been made to investigate this relationship in forward modeling and/or structural health monitoring techniques. This can be attributed to the… More >

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