K. Babu^1,*, C. Kumar², C. Kannaiyaraju³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756

Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component analysis-based dimensionality reduction techniques are… More >

R. K. Rojin^1,*, M. Mary Linda²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 245-258, 2022, DOI:10.32604/iasc.2022.021834

Abstract Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm Optimization (MPSO) algorithm to alleviate… More >

Muhammad Adnan Khan^1,2, Asma Kanwal³, Sagheer Abbas³, Faheem Khan⁴, T. Whangbo^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3607-3619, 2022, DOI:10.32604/cmc.2022.023480

Abstract Cloud computing is providing IT services to its customer based on Service level agreements (SLAs). It is important for cloud service providers to provide reliable Quality of service (QoS) and to maintain SLAs accountability. Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it. Cloud users’ major concerns; the factors for service reliability are based on response time, accessibility, availability, and speed. In this paper, we, therefore, experiment with the parallel mutant-Particle swarm optimization (PSO) for the detection and predictions of QoS violations in terms of response time, speed,… More >

Liang Jin^1,*, Qinghui Meng¹, Shuang Liang²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 387-395, 2022, DOI:10.32604/csse.2022.017745

Abstract The energy consumption of train operation occupies a large proportion of the total consumption of railway transportation. In order to improve the operating energy utilization rate of trains, a multi-objective particle swarm optimization (MPSO) algorithm with energy consumption, punctuality and parking accuracy as the objective and safety as the constraint is built. To accelerate its the convergence process, the train operation progression is divided into several modes according to the train speed-distance curve. A human-computer interactive particle swarm optimization algorithm is proposed, which presents the optimized results after a certain number of iterations to the decision maker, and the satisfactory… More >

Guize Liu^1,2, Jinqing Ye², Yuan Chen², Xiaolong Yang², Yanbin Gu^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 315-329, 2022, DOI:10.32604/cmes.2022.016224

Abstract This study explores the loss or degradation of the ecosystem and its service function in the Liaohe estuary coastal zone due to the deterioration of water quality. A prediction system based on support vector machine (SVM)-particle swarm optimization (PSO) (SVM-PSO) algorithm is proposed under the background of deep learning. SVM-PSO algorithm is employed to analyze the pollution status of the Liaohe estuary, so is the difference in water pollution of different sea consuming types. Based on the analysis results for causes of pollution, the control countermeasures of water pollution in Liaohe estuary are put forward. The results suggest that the… More >

P. Hemalatha^1,*, K. Dhanalakshmi²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 811-825, 2022, DOI:10.32604/iasc.2022.020973

Abstract Wireless sensor networks (WSNs) develop IoT (Internet of Things) that carry out an important part and include low-cost intelligent devices to gather information. However, these modern accessories have limitations concerning calculation, time taken for processing, storage capacity, and vitality sources. In addition to such restrictions, the foremost primary challenge for sensor networks is achieving reliable data transfer with the secured transmission in a hostile ambience containing vulnerable nodes. The proposed work initially analyses the relation between deployment configuration, lifetime of the deployed network, and transmission delay with this motivation. Besides, it also introduces a new cellular automata-based scheme for improving… More >

Muhammad Ali Ismail^*, Maria Waqas, Farah Sadiq

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1143-1155, 2022, DOI:10.32604/csse.2022.021604

Abstract The N-body problem in classical physics, is the calculation of force of gravitational attraction of heavenly bodies towards each other. Solving this problem for many heavenly bodies has always posed a challenge to physicists and mathematicians. Large number of bodies, huge masses, long distances and exponentially increasing number of equations of motion of the bodies have been the major hurdles in solving this problem for large and complex galaxies. Advent of high performance computational machines have mitigated the problem to much extent, but still for large number of bodies it consumes huge amount of resources and days for computation. Conventional… More >

Noor Gul^1,2, Saeed Ahmed^1,3, Atif Elahi⁴, Su Min Kim¹, Junsu Kim^1,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 369-387, 2022, DOI:10.32604/cmc.2022.022260

Abstract Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is still a major concern for… More >

Abdullah Shoukat¹, Muhammad Ali Mughal^1,*, Saifullah Younus Gondal¹, Farhana Umer², Tahir Ejaz³, Ashiq Hussain¹

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 269-285, 2022, DOI:10.32604/cmc.2022.021575

Abstract Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using the input-output quantities i.e., voltages,… More >

M. Rajalakshmi¹, V. Saravanan², V. Arunprasad³, C. A. T. Romero⁴, O. I. Khalaf⁵, C. Karthik^1,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 339-359, 2022, DOI:10.32604/iasc.2022.021696

Abstract In sugar production, model parameter estimation and controller tuning of the nonlinear clarification process are major concerns. Because the sugar industry’s clarification process is difficult and nonlinear, obtaining the exact model using identification methods is critical. For regulating the clarification process and identifying the model parameters, this work presents a state transition algorithm (STA). First, the model parameters for the clarifier are estimated using the normal system identification process. The STA is then utilized to improve the accuracy of the system parameters that have been identified. Metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and State Transition… More >