C. Nandagopal^1,*, P. Siva Kumar², R. Rajalakshmi³, S. Anandamurugan⁴

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 113-126, 2023, DOI:10.32604/iasc.2023.031103

Abstract Vehicle Ad hoc Networks (VANETs) have high mobility and a randomized connection structure, resulting in extremely dynamic behavior. Several challenges, such as frequent connection failures, sustainability, multi-hop data transfer, and data loss, affect the effectiveness of Transmission Control Protocols (TCP) on such wireless ad hoc networks. To avoid the problem, in this paper, mobility-aware zone-based routing in VANET is proposed. To achieve this concept, in this paper hybrid optimization algorithm is presented. The hybrid algorithm is a combination of Ant colony optimization (ACO) and artificial bee colony optimization (ABC). The proposed hybrid algorithm is designed for the routing process which… More >

Hadi Givi¹, Marie Hubalovska^2,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 179-202, 2023, DOI:10.32604/cmc.2023.030379

Abstract Metaheuristic algorithms are widely used in solving optimization problems. In this paper, a new metaheuristic algorithm called Skill Optimization Algorithm (SOA) is proposed to solve optimization problems. The fundamental inspiration in designing SOA is human efforts to acquire and improve skills. Various stages of SOA are mathematically modeled in two phases, including: (i) exploration, skill acquisition from experts and (ii) exploitation, skill improvement based on practice and individual effort. The efficiency of SOA in optimization applications is analyzed through testing this algorithm on a set of twenty-three standard benchmark functions of a variety of unimodal, high-dimensional multimodal, and fixed-dimensional multimodal… More >

Fangwei Zhang^1,2,*, Shihe Xu³, Bing Han⁴, Liming Zhang², Jun Ye⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2211-2226, 2023, DOI:10.32604/cmes.2022.022418

Abstract In optimization theory, the adaptive control of the optimization process is an important goal that people pursue. To solve this problem, this study introduces the idea of neutrosophic decision-making into classical heuristic algorithm, and proposes a novel neutrosophic adaptive clustering optimization thought, which is applied in a novel neutrosophic genetic algorithm (NGA), for example. The main feature of NGA is that the NGA treats the crossover effect as a neutrosophic fuzzy set, the variation ratio as a structural parameter, the crossover effect as a benefit parameter and the variation effect as a cost parameter, and then a neutrosophic fitness function… More >

Ceren Baştemur Kaya¹, Ebubekir Kaya^2,*, Göksel Gökkuş³

Computer Systems Science and Engineering, Vol.45, No.1, pp. 69-84, 2023, DOI:10.32604/csse.2023.030598

Abstract It is one of the topics that have been studied extensively on maximum power point tracking (MPPT) recently. Traditional or soft computing methods are used for MPPT. Since soft computing approaches are more effective than traditional approaches, studies on MPPT have shifted in this direction. This study aims comparison of performance of seven meta-heuristic training algorithms in the neuro-fuzzy training for MPPT. The meta-heuristic training algorithms used are particle swarm optimization (PSO), harmony search (HS), cuckoo search (CS), artificial bee colony (ABC) algorithm, bee algorithm (BA), differential evolution (DE) and flower pollination algorithm (FPA). The antecedent and conclusion parameters of… More >

C. P. Thamil Selvi^1,*, R. PushpaLakshmi²

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2439-2456, 2023, DOI:10.32604/csse.2023.029254

Abstract One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics. Bigdata is created from social websites like Facebook, WhatsApp, Twitter, etc. Opinions about products, persons, initiatives, political issues, research achievements, and entertainment are discussed on social websites. The unique data analytics method cannot be applied to various social websites since the data formats are different. Several approaches, techniques, and tools have been used for big data analytics, opinion mining, or sentiment analysis, but the accuracy is yet to be improved. The proposed work is motivated to do sentiment analysis on Twitter data… More >

A. Durgadevi^*, N. Shanmugavadivoo

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1951-1971, 2023, DOI:10.32604/csse.2023.026810

Abstract

Contemporarily, the development of distributed generations (DGs) technologies is fetching more, and their deployment in power systems is becoming broad and diverse. Consequently, several glitches are found in the recent studies due to the inappropriate/inadequate penetrations. This work aims to improve the reliable operation of the power system employing reliability indices using a metaheuristic-based algorithm before and after DGs penetration with feeder system. The assessment procedure is carried out using MATLAB software and Modified Salp Swarm Algorithm (MSSA) that helps assess the Reliability indices of the proposed integrated IEEE RTS79 system for seven different configurations. This algorithm modifies two control… More >

Tao Wu¹, Xinyu Wu¹, Jingjue Chen¹, Xi Chen^2,*, Amir Homayoon Ashrafzadeh³

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2879-2896, 2022, DOI:10.32604/cmc.2022.028942

Abstract Metaheuristic algorithm is a generalization of heuristic algorithm that can be applied to almost all optimization problems. For optimization problems, metaheuristic algorithm is one of the methods to find its optimal solution or approximate solution under limited conditions. Most of the existing metaheuristic algorithms are designed for serial systems. Meanwhile, existing algorithms still have a lot of room for improvement in convergence speed, robustness, and performance. To address these issues, this paper proposes an easily parallelizable metaheuristic optimization algorithm called team competition and cooperation optimization (TCCO) inspired by the process of human team cooperation and competition. The proposed algorithm attempts… More >

Esam A. AlQaralleh¹, Fahad Aldhaban², Halah Nasseif², Bassam A.Y. Alqaralleh^2,*, Tamer AbuKhalil³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5727-5740, 2022, DOI:10.32604/cmc.2022.026780

Abstract Recent technological advancements have been used to improve the quality of living in smart cities. At the same time, automated detection of vehicles can be utilized to reduce crime rate and improve public security. On the other hand, the automatic identification of vehicle license plate (LP) character becomes an essential process to recognize vehicles in real time scenarios, which can be achieved by the exploitation of optimal deep learning (DL) approaches. In this article, a novel hybrid metaheuristic optimization based deep learning model for automated license plate character recognition (HMODL-ALPCR) technique has been presented for smart city environments. The major… More >

Nawaf Alhebaishi¹, Abdulrhman M. Alshareef¹, Tawfiq Hasanin¹, Raed Alsini¹, Gyanendra Prasad Joshi², Seongsoo Cho³, Doo Ill Chul^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5233-5250, 2022, DOI:10.32604/cmc.2022.025596

Abstract In recent times, internet of things (IoT) applications on the cloud might not be the effective solution for every IoT scenario, particularly for time sensitive applications. A significant alternative to use is edge computing that resolves the problem of requiring high bandwidth by end devices. Edge computing is considered a method of forwarding the processing and communication resources in the cloud towards the edge. One of the considerations of the edge computing environment is resource management that involves resource scheduling, load balancing, task scheduling, and quality of service (QoS) to accomplish improved performance. With this motivation, this paper presents new… More >

Wenjun Li¹, Siyang Zhang¹, Guangwei Wu², Aldosary Saad³, Amr Tolba^3,4, Gwang-jun Kim^5,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4215-4231, 2022, DOI:10.32604/cmc.2022.024204

Abstract Recently, the development of Industrial Internet of Things has taken the advantage of 5G network to be more powerful and more intelligent. However, the upgrading of 5G network will cause a variety of issues increase, one of them is the increased cost of coverage. In this paper, we propose a sustainable wireless sensor networks system, which avoids the problems brought by 5G network system to some extent. In this system, deploying relays and selecting routing are for the sake of communication and charging. The main aim is to minimize the total energy-cost of communication under the precondition, where each terminal… More >