Shasha Zhao^1,2,3,*, Huanwen Yan^1,2, Qifeng Lin^1,2, Xiangnan Feng^1,2, He Chen^1,2, Dengyin Zhang^1,2

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1135-1156, 2024, DOI:10.32604/cmc.2024.045660

Abstract Task scheduling plays a key role in effectively managing and allocating computing resources to meet various computing tasks in a cloud computing environment. Short execution time and low load imbalance may be the challenges for some algorithms in resource scheduling scenarios. In this work, the Hierarchical Particle Swarm Optimization-Evolutionary Artificial Bee Colony Algorithm (HPSO-EABC) has been proposed, which hybrids our presented Evolutionary Artificial Bee Colony (EABC), and Hierarchical Particle Swarm Optimization (HPSO) algorithm. The HPSO-EABC algorithm incorporates both the advantages of the HPSO and the EABC algorithm. Comprehensive testing including evaluations of algorithm convergence speed, resource execution time, load balancing,… More >

Qiangfei Cao¹, Huilai Wang², Zijia Hui¹, Lingyun Chen^2,*

Energy Engineering, Vol.121, No.2, pp. 499-521, 2024, DOI:10.32604/ee.2023.042702

Abstract Distribution generation (DG) technology based on a variety of renewable energy technologies has developed rapidly. A large number of multi-type DG are connected to the distribution network (DN), resulting in a decline in the stability of DN operation. It is urgent to find a method that can effectively connect multi-energy DG to DN. photovoltaic (PV), wind power generation (WPG), fuel cell (FC), and micro gas turbine (MGT) are considered in this paper. A multi-objective optimization model was established based on the life cycle cost (LCC) of DG, voltage quality, voltage fluctuation, system network loss, power deviation of the tie-line, DG… More >

Yazeed Yasin Ghadi¹, Mohammed S. Alshehri², Sultan Almakdi², Oumaima Saidani^3,*, Nazik Alturki³, Fawad Masood⁴, Muhammad Shahbaz Khan⁵

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 781-797, 2023, DOI:10.32604/cmc.2023.042777

Abstract Securing digital image data is a key concern in today’s information-driven society. Effective encryption techniques are required to protect sensitive image data, with the Substitution-box (S-box) often playing a pivotal role in many symmetric encryption systems. This study introduces an innovative approach to creating S-boxes for encryption algorithms. The proposed S-boxes are tested for validity and non-linearity by incorporating them into an image encryption scheme. The nonlinearity measure of the proposed S-boxes is 112. These qualities significantly enhance its resistance to common cryptographic attacks, ensuring high image data security. Furthermore, to assess the robustness of the S-boxes, an encryption system… More >

Huaixi Xing^*, Qinghua Xing

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2685-2705, 2023, DOI:10.32604/cmc.2023.036223

Abstract With the advancement of combat equipment technology and combat concepts, new requirements have been put forward for air defense operations during a group target attack. To achieve high-efficiency and low-loss defensive operations, a reasonable air defense weapon assignment strategy is a key step. In this paper, a multi-objective and multi-constraints weapon target assignment (WTA) model is established that aims to minimize the defensive resource loss, minimize total weapon consumption, and minimize the target residual effectiveness. An optimization framework of air defense weapon mission scheduling based on the multi-objective artificial bee colony (MOABC) algorithm is proposed. The solution for point-to-point saturated… More >

Hang Yang^1,2,*, Xunbo Li¹, Witold Pedrycz²

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1531-1551, 2023, DOI:10.32604/iasc.2023.039256

Abstract Energy supply is one of the most critical challenges of wireless sensor networks (WSNs) and industrial wireless sensor networks (IWSNs). While research on coverage optimization problem (COP) centers on the network’s monitoring coverage, this research focuses on the power banks’ energy supply coverage. The study of 2-D and 3-D spaces is typical in IWSN, with the realistic environment being more complex with obstacles (i.e., machines). A 3-D surface is the field of interest (FOI) in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN. The hybrid power bank deployment model is… More >

S. S. Selva Pradeep^*, M. Marsaline Beno

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1757-1770, 2022, DOI:10.32604/iasc.2022.023470

Abstract The Brushless Direct Current (BLDC) motors have shown to be a cost-effective alternative to traditional motors. The smooth and efficient operation of the BLDC motor is dependent on speed regulation. This research proposes a sensorless intelligent speed control technique for BLDC using an Adaptive Network-based Fuzzy Inference Systems (ANFIS) based Artificial Bee Colony (ABC) algorithm. The motor’s back EMF is measured, and ANFIS is used to generate Hall signals. The ABC is then utilized to provide the pulses needed for the three-phase inverter, avoiding the requirement of logic gate circuits. The input DC voltage to the inverter is controlled by… More >

C. Ram Kumar^1,*, K. Murali Krishna², Mohammad Shabbir Alam³, K. Vigneshwaran⁴, Sridharan Kannan⁵, C. Bharatiraja⁶

Computer Systems Science and Engineering, Vol.43, No.1, pp. 259-273, 2022, DOI:10.32604/csse.2022.023477

Abstract The Wireless Sensor Networks (WSN) is a self-organizing network with random deployment of wireless nodes that connects each other for effective monitoring and data transmission. The clustering technique employed to group the collection of nodes for data transmission and each node is assigned with a cluster head. The major concern with the identification of the cluster head is the consideration of energy consumption and hence this paper proposes an hybrid model which forms an energy efficient cluster head in the Wireless Sensor Network. The proposed model is a hybridization of Glowworm Swarm Optimization (GSO) and Artificial Bee Colony (ABC) algorithm… More >

Ayat Alrosan¹, Waleed Alomoush², Mohammed Alswaitti^3,*, Khalid Alissa⁴, Shahnorbanun Sahran⁵, Sharif Naser Makhadmeh⁶, Kamal Alieyan⁷

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1575-1593, 2021, DOI:10.32604/cmc.2021.015925

Abstract Fuzzy C-means (FCM) is a clustering method that falls under unsupervised machine learning. The main issues plaguing this clustering algorithm are the number of the unknown clusters within a particular dataset and initialization sensitivity of cluster centres. Artificial Bee Colony (ABC) is a type of swarm algorithm that strives to improve the members’ solution quality as an iterative process with the utilization of particular kinds of randomness. However, ABC has some weaknesses, such as balancing exploration and exploitation. To improve the exploration process within the ABC algorithm, the mean artificial bee colony (MeanABC) by its modified search equation that depends… More >

Hui Zhi^1,2, Sanyang Liu¹

Intelligent Automation & Soft Computing, Vol.25, No.4, pp. 815-825, 2019, DOI:10.31209/2019.100000085

Abstract In this paper, we proposed a hybrid algorithm, which is embedding the genetic operators in the global-best-guided artificial bee colony algorithms called GABCGA to solve the nonlinear design optimization problems. The genetic algorithm has no memory function and good at find global optimization with large probability, but the artificial bee colony algorithm not have selection, crossover and mutation operator and most significant at local search. The hybrid algorithm balances the exploration and exploitation ability further by combining the advantages of both. The experimental results of five engineering optimization and comparisons with existing approaches show that the proposed approach is outperforms… More >

Peizhong Liu¹, Xiaofang Liu¹, Yanming Luo², Yongzhao Du¹, Yulin Fan¹, Hsuan‐Ming Feng³

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 385-394, 2019, DOI:10.31209/2019.100000100

Abstract Aiming at the drawback of artificial bee colony algorithm (ABC) with slow convergence speed and weak exploitation capacity, an enhanced exploitation artificial bee colony algorithm is proposed, EeABC for short. Firstly, a generalized opposition-based learning strategy (GOBL) is employed when initial population is produced for obtaining an evenly distributed population. Subsequently, inspired by the differential evolution (DE), two new search equations are proposed, where the one is guided by the best individuals in the next generation to strengthen exploitation and the other is to avoid premature convergence. Meanwhile, the distinction between the employed bee and the onlooker bee is not… More >