Raniyah Wazirali^*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1429-1445, 2021, DOI:10.32604/cmc.2021.014172 - 05 February 2021

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… 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 - 23 December 2020

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 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 - 26 November 2020

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… 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 - 26 November 2020

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 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 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 - 18 September 2020

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… 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 - 16 September 2020

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… 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 - 16 September 2020

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 More >

Mehiar, D.A.F., Azizul, Z.H.^*, Loo, C.K.

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 447-454, 2020, DOI:10.32604/iasc.2020.013921

Abstract In this paper we show how the quantum-based particle swarm optimization (QPSO) method is adopted to derive a new derivation for robotics application in search and rescue simulations. The new derivation, called the Quantum Robot Darwinian PSO (QRDPSO) is inspired from another PSO-based algorithm, the Robot Darwinian PSO (RDPSO). This paper includes comprehensive details on the QRDPSO formulation and parameters control which show how the swarm overcomes communication constraints to avoid obstacles and achieve optimal solution. The results show the QRDPSO is an upgrade over RDPSO in terms of convergence speed, trajectory control, obstacle avoidance More >

Vijayalakshmi. K^1,*, Anandan. P²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 303-311, 2020, DOI:10.31209/2020.100000165

Abstract The advent of sensors that are light in weight, small-sized, low power and are enabled by wireless network has led to growth of Wireless Sensor Networks (WSNs) in multiple areas of applications. The key problems faced in WSNs are decreased network lifetime and time delay in transmission of data. Several key issues in the WSN design can be addressed using the Multi-Objective Optimization (MOO) Algorithms. The selection of the Cluster Head is a NP Hard optimization problem in nature. The CH selection is also challenging as the sensor nodes are organized in clusters. Through partitioning… More >