NSTL国家科技图书文献中心

1. Automated design of state transition rules in ant colony optimization by genetic programming: a comprehensive investigation NSTL国家科技图书文献中心

Lin, Bo-Cheng | Mei, Yi ... - 《Memetic computing》 - 2025,17(1) - 共22页

摘要：The automated design of Ant Colony | Optimization (ACO) algorithms has become increasingly | GP-ACO* in the Max-Min Ant System; additional global* | combinatorial optimization* problems. Although existing methods* | design state transition rules of ACO. However, existing

关键词： Ant colony optimization (ACO) | Genetic programming (GP) | Combinatorial optimization | Travelling salesman problem | Hyper-heuristic

2. Real-time Path Re-planning to Deal with Dynamic Obstacles Using a Parallel Probabilistic Roadmap NSTL国家科技图书文献中心

Geemoon Noh | Jihoon Park ... - 《International Journal of Aeronautical and Space Sciences》 - 2025,26(2) - 748～759 - 共12页

摘要：, we utilize the Ant Colony Optimization (ACO | problem. Within ACO, genetic algorithm mutation methods | elitist ant* system is applied to enhance convergence* | With the advancement of UAV performance, there | has been a growing need for efficient path and

关键词： Ant colony optimization (ACO) | Parallel computing | Probabilistic roadmap (PRM) | Unmanned aerial vehicle (UAV)

3. RSSI-Based Indoor Distance Estimation in Wi-Fi IoT Application Using AI Approaches NSTL国家科技图书文献中心

Sarika Mane | Makarand Kulkarni ... - 《International journal of communication systems》 - 2025,38(5) - e70008.1～e70008.19 - 共19页

摘要： neighbor (KNN), Gaussian process (GP), and ant colony | optimization (ACO) are used to train the models to correlate | respect to earlier reported work. ACO* achieves a 78.61* | In many Internet of Things (IoT) applications | , device tracking is required to improve localization

关键词： ant colony optimization (ACO) | distance estimation | Internet of Things (IoT) | mean absolute error (MAE) | received signal strength indicator (RSSI)

4. Path Optimization Method Under UAV Charging Scheduling Network NSTL国家科技图书文献中心

Tingting Yang | Yiqian Wang ... - 《Algorithms and Architectures for Parallel Processing,Part II》 - International Conference on Algorithms and Architectures for Parallel Processing - 2025, - 238～253 - 共16页

摘要：-energy state. An Ant* Colony Optimization-based UAV | Trajectory Planning and Charging Scheduling (ACO-TPCS | framework of the ACO-TPCS algorithm consists of several | matrix construction, ant generation, feasible solution* | demonstrate the effectiveness of the ACO-TPCS algorithm in

关键词： UAVs | Trajectory planning | Charging scheduling | Charging network | Ant colony optimization (ACO)

5. Neural network and ACO algorithm-tuned PI controller for MPPT in a hybrid battery-supercapacitor energy storage system within DC micro-grid photovoltaic installations NSTL国家科技图书文献中心

Benfatma, Hadjer | Khouidmi, Houari ... - 《Journal of Energy Storage》 - 2025,120(Jun.) - 1.1～1.18 - 共18页

摘要： Feedforward Neural Network (FNN) with an Ant Colony | Optimization (ACO)-tuned Proportional-Integral (PI | The efficiency and stability of standalone | photovoltaic (PV) systems depend heavily on the effectiveness | of Maximum Power Point Tracking (MPPT) techniques

关键词： Maximum Power Point Tracking (MPPT) | Perturb and Observe P & | Particle Swarm Optimization (PSO) | Ant Colony Optimization (ACO) | Feedforward Neural Network (FNN) | Photovoltaic (PV) systems | Hybrid energy storage systems | POINT TRACKING TECHNIQUES | POWER | SEARCH

6. Optimizing edge server placement and load distribution in mobile edge computing using ACO and heuristic algorithms NSTL国家科技图书文献中心

Sevda Zarei | Sadoon Azizi ... - 《The Journal of Supercomputing》 - 2025,81(1) - 257.1～257.32 - 共32页

摘要： problems, we propose an ant colony optimization (ACO | With the rapid growth and development of | Internet of Things (IoT) and smart mobile devices, the | volume of data generated at the network edge has | increased significantly. Mobile edge computing (MEC) has

关键词： Internet of Things (IoT) | Mobile edge computing (MEC) | Edge server placement | Load distribution | Ant colony optimization (ACO) | Quality of service (QoS) | Load balancing

7. Seismic performance-based design optimization of 2D steel chevron-braced frames using ACO algorithm and nonlinear pushover analysis NSTL国家科技图书文献中心

Faghirnejad, Saba | Kontoni, Denise-Pene...... - 《Structural and multidisciplinary optimization》 - 2025,68(1) - 共27页 - 被引量：1

摘要： colony metaheuristic optimization algorithm is employed | , optimization* techniques, and optimality criteria methods to* | automatically design the pushover drift performance. An ant | optimization codes in MATLAB and OpenSees for conducting the | optimization problem. In the second step, a nonlinear

关键词： Optimization | Ant colony optimization (ACO) | Steel-braced frame structures | Nonlinear pushover analysis | Seismic design | Performance-based design

8. Ant Colony Optimized Extended Kalman Filter for State of Charge Estimation of Lithium-Ion Batteries NSTL国家科技图书文献中心

Kannan, M. | Sundareswaran, K.... - 《IEEE Transactions on Instrumentation and Measurement》 - 2025,74(Pt.1) - 2000410.1～2000410.10 - 共10页

摘要： of ant* colony optimized (ACO) extended Kalman* | ) error covariances, are fine-tuned using the ACO | an optimization* problem. The proposed method has* | , the effectiveness of the ACO-tuned EKF approach is | This work reports the practical implementation

关键词： Batteries | Estimation | Battery charge measurement | Mathematical models | Kalman filters | Voltage measurement | Temperature measurement | Noise measurement | Noise | Filtering algorithms...

9. Optimization assisted probabilistic damage localization of cracks in weld connections of a steel portal frame using electromechanical impedance technique NSTL国家科技图书文献中心

Kamal, Mayank | Parida, Lukesh ... - 《Smart Materials & Structures》 - 2025,34(3) - 共19页

摘要： particle swarm optimization (PSO), ant colony | optimization, and artificial bee colony optimization (ABC | utilizes swarm optimization* based on wavelet damage* | . Further, various swarm optimization* algorithms like* | that PSO-based optimization* using wavelet*

关键词： structural health monitoring (SHM) | damage identification | electromechanical impedance (EMI) | discrete wavelet transform (DWT) | particle swarm optimization (PSO) | ant colony optimization (ACO) | artificial bee colony optimization (ABC)

10. Improved strategy of ant colony optimization for path planning via stochastic pheromone updating and cyclic initialization NSTL国家科技图书文献中心

Fang, Shengkun | Deng, Zhiwen ... - 《Journal of Mechanical Science and Technology》 - 2025,39(4) - 2051～2062 - 共12页

摘要：The ant* colony optimization (ACO) algorithm is* | commonly used for path optimization* to reduce the* | , frequently arise. In this study, we propose an optimization | strategy for ACO to improve the performance of the ACO | increasing the cyclic initial state. Algorithm optimization

摘要：The automated design of Ant Colony | Optimization (ACO) algorithms has become increasingly | GP-ACO* in the Max-Min Ant System; additional global* | combinatorial optimization* problems. Although existing methods* | design state transition rules of ACO. However, existing

关键词： Ant colony optimization (ACO) | Genetic programming (GP) | Combinatorial optimization | Travelling salesman problem | Hyper-heuristic

摘要：, we utilize the Ant Colony Optimization (ACO | problem. Within ACO, genetic algorithm mutation methods | elitist ant* system is applied to enhance convergence* | With the advancement of UAV performance, there | has been a growing need for efficient path and

关键词： Ant colony optimization (ACO) | Parallel computing | Probabilistic roadmap (PRM) | Unmanned aerial vehicle (UAV)

摘要： neighbor (KNN), Gaussian process (GP), and ant colony | optimization (ACO) are used to train the models to correlate | respect to earlier reported work. ACO* achieves a 78.61* | In many Internet of Things (IoT) applications | , device tracking is required to improve localization

关键词： ant colony optimization (ACO) | distance estimation | Internet of Things (IoT) | mean absolute error (MAE) | received signal strength indicator (RSSI)

摘要：-energy state. An Ant* Colony Optimization-based UAV | Trajectory Planning and Charging Scheduling (ACO-TPCS | framework of the ACO-TPCS algorithm consists of several | matrix construction, ant generation, feasible solution* | demonstrate the effectiveness of the ACO-TPCS algorithm in

关键词： UAVs | Trajectory planning | Charging scheduling | Charging network | Ant colony optimization (ACO)

摘要： Feedforward Neural Network (FNN) with an Ant Colony | Optimization (ACO)-tuned Proportional-Integral (PI | The efficiency and stability of standalone | photovoltaic (PV) systems depend heavily on the effectiveness | of Maximum Power Point Tracking (MPPT) techniques

关键词： Maximum Power Point Tracking (MPPT) | Perturb and Observe P & | Particle Swarm Optimization (PSO) | Ant Colony Optimization (ACO) | Feedforward Neural Network (FNN) | Photovoltaic (PV) systems | Hybrid energy storage systems | POINT TRACKING TECHNIQUES | POWER | SEARCH

摘要： problems, we propose an ant colony optimization (ACO | With the rapid growth and development of | Internet of Things (IoT) and smart mobile devices, the | volume of data generated at the network edge has | increased significantly. Mobile edge computing (MEC) has

关键词： Internet of Things (IoT) | Mobile edge computing (MEC) | Edge server placement | Load distribution | Ant colony optimization (ACO) | Quality of service (QoS) | Load balancing

关键词： Optimization | Ant colony optimization (ACO) | Steel-braced frame structures | Nonlinear pushover analysis | Seismic design | Performance-based design

摘要： of ant* colony optimized (ACO) extended Kalman* | ) error covariances, are fine-tuned using the ACO | an optimization* problem. The proposed method has* | , the effectiveness of the ACO-tuned EKF approach is | This work reports the practical implementation

关键词： Batteries | Estimation | Battery charge measurement | Mathematical models | Kalman filters | Voltage measurement | Temperature measurement | Noise measurement | Noise | Filtering algorithms...

摘要： particle swarm optimization (PSO), ant colony | optimization, and artificial bee colony optimization (ABC | utilizes swarm optimization* based on wavelet damage* | . Further, various swarm optimization* algorithms like* | that PSO-based optimization* using wavelet*

关键词： structural health monitoring (SHM) | damage identification | electromechanical impedance (EMI) | discrete wavelet transform (DWT) | particle swarm optimization (PSO) | ant colony optimization (ACO) | artificial bee colony optimization (ABC)

摘要：The ant* colony optimization (ACO) algorithm is* | commonly used for path optimization* to reduce the* | , frequently arise. In this study, we propose an optimization | strategy for ACO to improve the performance of the ACO | increasing the cyclic initial state. Algorithm optimization

关键词： Stochastic pheromone | Ant colony algorithm | Local optimum | Cyclic initialization | Path optimization

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：The automated design of Ant Colony | Optimization (ACO) algorithms has become increasingly | GP-ACO in the Max-Min Ant System; additional global | combinatorial optimization problems. Although existing methods | design state transition rules of ACO. However, existing

关键词： Ant colony optimization (ACO) | Genetic programming (GP) | Combinatorial optimization | Travelling salesman problem | Hyper-heuristic

摘要：, we utilize the Ant Colony Optimization (ACO | problem. Within ACO, genetic algorithm mutation methods | elitist ant system is applied to enhance convergence | With the advancement of UAV performance, there | has been a growing need for efficient path and

关键词： Ant colony optimization (ACO) | Parallel computing | Probabilistic roadmap (PRM) | Unmanned aerial vehicle (UAV)

摘要： neighbor (KNN), Gaussian process (GP), and ant colony | optimization (ACO) are used to train the models to correlate | respect to earlier reported work. ACO achieves a 78.61 | In many Internet of Things (IoT) applications | , device tracking is required to improve localization

关键词： ant colony optimization (ACO) | distance estimation | Internet of Things (IoT) | mean absolute error (MAE) | received signal strength indicator (RSSI)

摘要：-energy state. An Ant Colony Optimization-based UAV | Trajectory Planning and Charging Scheduling (ACO-TPCS | framework of the ACO-TPCS algorithm consists of several | matrix construction, ant generation, feasible solution | demonstrate the effectiveness of the ACO-TPCS algorithm in

关键词： UAVs | Trajectory planning | Charging scheduling | Charging network | Ant colony optimization (ACO)

摘要： Feedforward Neural Network (FNN) with an Ant Colony | Optimization (ACO)-tuned Proportional-Integral (PI | The efficiency and stability of standalone | photovoltaic (PV) systems depend heavily on the effectiveness | of Maximum Power Point Tracking (MPPT) techniques

关键词： Maximum Power Point Tracking (MPPT) | Perturb and Observe P & | Particle Swarm Optimization (PSO) | Ant Colony Optimization (ACO) | Feedforward Neural Network (FNN) | Photovoltaic (PV) systems | Hybrid energy storage systems | POINT TRACKING TECHNIQUES | POWER | SEARCH

摘要： problems, we propose an ant colony optimization (ACO | With the rapid growth and development of | Internet of Things (IoT) and smart mobile devices, the | volume of data generated at the network edge has | increased significantly. Mobile edge computing (MEC) has

关键词： Internet of Things (IoT) | Mobile edge computing (MEC) | Edge server placement | Load distribution | Ant colony optimization (ACO) | Quality of service (QoS) | Load balancing

关键词： Optimization | Ant colony optimization (ACO) | Steel-braced frame structures | Nonlinear pushover analysis | Seismic design | Performance-based design

摘要： of ant colony optimized (ACO) extended Kalman | ) error covariances, are fine-tuned using the ACO | an optimization problem. The proposed method has | , the effectiveness of the ACO-tuned EKF approach is | This work reports the practical implementation

关键词： Batteries | Estimation | Battery charge measurement | Mathematical models | Kalman filters | Voltage measurement | Temperature measurement | Noise measurement | Noise | Filtering algorithms...

摘要： particle swarm optimization (PSO), ant colony | optimization, and artificial bee colony optimization (ABC | utilizes swarm optimization based on wavelet damage | . Further, various swarm optimization algorithms like | that PSO-based optimization using wavelet

关键词： structural health monitoring (SHM) | damage identification | electromechanical impedance (EMI) | discrete wavelet transform (DWT) | particle swarm optimization (PSO) | ant colony optimization (ACO) | artificial bee colony optimization (ABC)

摘要：The ant colony optimization (ACO) algorithm is | commonly used for path optimization to reduce the | , frequently arise. In this study, we propose an optimization | strategy for ACO to improve the performance of the ACO | increasing the cyclic initial state. Algorithm optimization

关键词： Stochastic pheromone | Ant colony algorithm | Local optimum | Cyclic initialization | Path optimization

4008-161-200 800-990-8900

国家科技图书文献中心

摘要：The automated design of Ant Colony | Optimization (ACO) algorithms has become increasingly | GP-ACO* in the Max-Min Ant System; additional global* | combinatorial optimization* problems. Although existing methods* | design state transition rules of ACO. However, existing

摘要：, we utilize the Ant Colony Optimization (ACO | problem. Within ACO, genetic algorithm mutation methods | elitist ant* system is applied to enhance convergence* | With the advancement of UAV performance, there | has been a growing need for efficient path and

摘要： neighbor (KNN), Gaussian process (GP), and ant colony | optimization (ACO) are used to train the models to correlate | respect to earlier reported work. ACO* achieves a 78.61* | In many Internet of Things (IoT) applications | , device tracking is required to improve localization

摘要：-energy state. An Ant* Colony Optimization-based UAV | Trajectory Planning and Charging Scheduling (ACO-TPCS | framework of the ACO-TPCS algorithm consists of several | matrix construction, ant generation, feasible solution* | demonstrate the effectiveness of the ACO-TPCS algorithm in

摘要： of ant* colony optimized (ACO) extended Kalman* | ) error covariances, are fine-tuned using the ACO | an optimization* problem. The proposed method has* | , the effectiveness of the ACO-tuned EKF approach is | This work reports the practical implementation

摘要： particle swarm optimization (PSO), ant colony | optimization, and artificial bee colony optimization (ABC | utilizes swarm optimization* based on wavelet damage* | . Further, various swarm optimization* algorithms like* | that PSO-based optimization* using wavelet*

摘要：The ant* colony optimization (ACO) algorithm is* | commonly used for path optimization* to reduce the* | , frequently arise. In this study, we propose an optimization | strategy for ACO to improve the performance of the ACO | increasing the cyclic initial state. Algorithm optimization