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 >

Nabeela Awan¹, Salman Khan², Mohammad Khalid Imam Rahmani³, Muhammad Tahir³, Nur Alam MD^4,*, Ryan Alturki⁵, Ihsan Ullah⁶

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2449-2462, 2021, DOI:10.32604/cmc.2021.014386

Abstract Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things (IoT). The IoT is the backbone of smart city applications such as smart grids and green energy management. In smart cities, the IoT devices are used for linking power, price, energy, and demand information for smart homes and home energy management (HEM) in the smart grids. In complex smart grid-connected systems, power scheduling and secure dispatch of information are the main research challenge. These challenges can be resolved through various machine learning techniques and data analytics. In this paper, we have proposed a particle… More >

Raniyah Wazirali^*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1429-1445, 2021, DOI:10.32604/cmc.2021.014172

Abstract Intrusion detection system (IDS) techniques are used in cybersecurity to protect and safeguard sensitive assets. The increasing network security risks can be mitigated by implementing effective IDS methods as a defense mechanism. The proposed research presents an IDS model based on the methodology of the adaptive fuzzy k-nearest neighbor (FKNN) algorithm. Using this method, two parameters, i.e., the neighborhood size (k) and fuzzy strength parameter (m) were characterized by implementing the particle swarm optimization (PSO). In addition to being used for FKNN parametric optimization, PSO is also used for selecting the conditional feature subsets for detection. To proficiently regulate the… More >

Xueqing Wang¹, Shuang Liu^1,*, Lejun Zhang²

Computer Systems Science and Engineering, Vol.36, No.1, pp. 259-269, 2021, DOI:10.32604/csse.2021.014343

Abstract The cost of highway is affected by many factors. Its composition and calculation are complicated and have great ambiguity. Calculating the cost of highway according to the traditional highway engineering estimation method is a completely tedious task. Constructing a highway cost prediction model can forecast the value promptly and improve the accuracy of highway engineering cost. This work sorts out and collects 60 sets of measured data of highway engineering; establishes an expressway cost index system based on 10 factors, including main route mileage, roadbed width, roadbed earthwork, and number of bridges; and processes the data through principal component analysis… More >

Jingxin Yu^1,3, Wengang Zheng^1,*, Linlin Xu³, Lili Zhangzhong¹, Geng Zhang², Feifei Shan¹

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 989-1003, 2020, DOI:10.32604/iasc.2020.010130

Abstract Accurate estimation of reference evapotranspiration (ET0) is a critical prerequisite for the development of agricultural water management strategies. It is challenging to estimate the ET0 of a solar greenhouse because of its unique environmental variations. Based on the idea of ensemble learning, this paper proposed a novel ET0i estimation model named PSO-XGBoost, which took eXtreme Gradient Boosting (XGBoost) as the main regression model and used Particle Swarm Optimization (PSO) algorithm to optimize the parameters of XGBoost. Using the meteorological and soil moisture data during the two-crop planting process as the experimental data, and taking ET0i calculated based on the improved… More >

Deepak Prashar¹, Gyanendra Prasad Joshi², Sudan Jha¹, Eunmok Yang³, Kwang Chul Son^4,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1529-1549, 2021, DOI:10.32604/cmc.2020.012986

Abstract The Internet of Things (IoT) is envisioned as a network of various wireless sensor nodes communicating with each other to offer state-of-the-art solutions to real-time problems. These networks of wireless sensors monitor the physical environment and report the collected data to the base station, allowing for smarter decisions. Localization in wireless sensor networks is to localize a sensor node in a two-dimensional plane. However, in some application areas, such as various surveillances, underwater monitoring systems, and various environmental monitoring applications, wireless sensors are deployed in a three-dimensional plane. Recently, localization-based applications have emerged as one of the most promising services… More >

G. Mousa¹, Amr Almaddah², Ayman A. Aly^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2005-2023, 2021, DOI:10.32604/cmc.2020.012580

Abstract About 10–20% of every country’s population is disable. There are at least 650 million people with a kind of disability worldwide. Assistance and support are perquisites for many handicap people for participating in society. Electric powered wheelchairs provide efficient mobility to motor impaired persons. In this paper a smart controller of a wheel chair mobile robot using Particle Swarm Optimization Proportional controller (PSO-P) was proposed where (PSO) algorithm was utilized to tune the proportional controller’s gains for each axis. Aiming to improve wheelchair tracking trajectory, a kinematic model of a robot with linear and angular velocities parameters was developed. The… More >

Shifu Xu^*, Yanan Jiang

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 401-415, 2020, DOI:10.32604/cmes.2020.09608

Abstract Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize, the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied. The kinematic diagram of redundant manipulator is created, to derive the equation of motion trajectory of redundant manipulator end. Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy. Based on the tracking ellipse of redundant manipulator, the tracking shape of redundant manipulator is determined with the overall tracking index as the second index, and the optimization method of tracking index is… More >

Huaixi Xing¹, Yu Zhao¹, Yuhui Zhang¹, You Chen^{1, *}

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2295-2308, 2020, DOI:10.32604/cmc.2020.011858

Abstract Aiming at the yaw problem caused by inertial navigation system errors accumulation during the navigation of an intelligent aircraft, a three-dimensional trajectory planning method based on the particle swarm optimization-A star (PSO-A*) algorithm is designed. Firstly, an environment model for aircraft error correction is established, and the trajectory is discretized to calculate the positioning error. Next, the positioning error is corrected at many preset trajectory points. The shortest trajectory and the fewest correction times are regarded as optimization goals to improve the heuristic function of A star (A*) algorithm. Finally, the index weights are continuously optimized by the particle swarm… More >

Fengchang Xue^{1, *}, Juan Tian¹, Wei Wang², Yanran Zhang¹, Gohar Ali³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2189-2199, 2020, DOI:10.32604/cmc.2020.06513

Abstract For the challenge of parameter calibration in the process of SWMM (storm water management model) model application, we use particle Swarm Optimization (PSO) and Sequence Quadratic Programming (SQP) in combination to calibrate the parameters and get the optimal parameter combination in this research. Then, we compare and analyze the simulation result with the other two respectively using initial parameters and parameters obtained by PSO algorithm calibration alone. The result shows that the calibration result of PSO-SQP combined algorithm has the highest accuracy and shows highly consistent with the actual situation, which provides a scientific and effective new idea for parameter… More >