Junfeng Sun¹, Chenghai Li¹, Yafei Song^1,*, Peng Ni², Jian Wang¹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 993-1021, 2023, DOI:10.32604/csse.2023.039215

Abstract The accuracy of historical situation values is required for traditional network security situation prediction (NSSP). There are discrepancies in the correlation and weighting of the various network security elements. To solve these problems, a combined prediction model based on the temporal convolution attention network (TCAN) and bi-directional gate recurrent unit (BiGRU) network is proposed, which is optimized by singular spectrum analysis (SSA) and improved quantum particle swarm optimization algorithm (IQPSO). This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data. Furthermore, a prediction model of TCAN-BiGRU… More >

S. Pandeeswari^1,*, S. Jaganathan²

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2811-2825, 2023, DOI:10.32604/csse.2023.029945

Abstract The Brushless DC Motor drive systems are used widely with renewable energy resources. The power converter controlling technique increases the performance by novel techniques and algorithms. Conventional approaches are mostly focused on buck converter, Fuzzy logic control with various switching activity. In this proposed research work, the QPSO (Quantum Particle Swarm Optimization algorithm) is used on the switching state of converter from the generation unit of solar module. Through the duty cycle pulse from optimization function, the MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor) of the Boost converter gets switched when BLDC (Brushless Direct Current Motor) motor drive system requires power. Voltage Source… More >

Edgar Scavino^1,*, Mohd Amiruddin Abd Rahman¹, Zahid Farid²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 379-397, 2023, DOI:10.32604/cmc.2023.023824

Abstract Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.020613

Abstract This research uses the improved Quantum Particle Swarm Optimization (QPSO) algorithm to build an Internet of Things (IoT) life comfort monitoring system based on wireless sensing networks. The purpose is to improve the quality of intelligent life. The functions of the system include automatic basketball court lighting system, monitoring of infants’ sleeping posture and accidental falls of the elderly, human thermal comfort measurement and other related life comfort services, etc. On the hardware system of the IoT, this research is based on the latest version of ZigBee 3.0, which uses optical sensors, 3-axis accelerometers, and temperature/humidity sensors in the IoT… More >

Yong Xiao¹, Xin Jin¹, Jingfeng Yang², Yanhua Shen^3,*, Quansheng Guan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1293-1313, 2021, DOI:10.32604/cmes.2021.012562

Abstract User-transformer relations are significant to electric power marketing, power supply safety, and line loss calculations. To get accurate user-transformer relations, this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization (QPSO) and Fuzzy C-Means Clustering. The main idea is: as energy meters at different transformer areas exhibit different zero-crossing shift features, we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations. The proposed method contributes in three main ways. First, based on the fuzzy C-means clustering algorithm (FCM),… More >

Wei Zhang¹, Weifeng Shi², Bing Sun³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 423-431, 2019, DOI:10.31209/2018.100000045

Abstract An intelligent optimization algorithm for a marine generator excitation controller is proposed to improve dynamic performance of shipboard power systems. This algorithm combines a belief–desire–intention agent with a quantum-behaved particle swarm optimization (QPSO) algorithm to optimize a marine generator excitation controller. The shipboard zonal power system is simulated under disturbance due to load change or severe fault. The results show that the proposed optimization algorithm can improve marine generator stability compared with conventional excitation controllers under various operating conditions. Moreover, the proposed intelligent algorithm is highly robust because its performance is insensitive to the accuracy of system parameters. More >