Ahmed S. Ghiduk^1,2,*, Abdullah Alharbi¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 647-665, 2023, DOI:10.32604/iasc.2023.031865

Abstract Many search-based algorithms have been successfully applied in several software engineering activities. Genetic algorithms (GAs) are the most used in the scientific domains by scholars to solve software testing problems. They imitate the theory of natural selection and evolution. The harmony search algorithm (HSA) is one of the most recent search algorithms in the last years. It imitates the behavior of a musician to find the best harmony. Scholars have estimated the similarities and the differences between genetic algorithms and the harmony search algorithm in diverse research domains. The test data generation process represents a critical task in software validation.… More >

Zheng Wang^*, Shangke Liu, Yanli Xiao, Ye Wan, Bin Bai

Energy Engineering, Vol.119, No.6, pp. 2655-2679, 2022, DOI:10.32604/ee.2022.021843

Abstract Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply. Despite the complexity of their protection, as well as the operation of distributed generation resources in the distribution network, factors such as improving reliability, increasing production capacity of the distribution network, stabilizing the voltage of the distribution network, reducing peak clipping losses, as well as economic and environmental considerations, have expanded the influence of distributed generation (DG) resources in the distribution network. The location of DG sources and their capacity are the key factors… More >

Zinan Zhou, Yirun Chen, Wensheng Dai^*

Energy Engineering, Vol.119, No.6, pp. 2681-2709, 2022, DOI: 10.32604/ee.2022.021410

Abstract The use of different energy carriers together, known as an energy hub, has been a hot topic of research in recent years amongst scientists and researchers. The term energy hub refers to the simultaneous operation of various infrastructures for energy generation and transfer, which has gained momentum in the form of microgrids (MGs). This paper introduces a new strategy for the optimal performance of an MG consisting of different energy carriers for each day. In a smart distribution network (DN), MGs can reduce their own costs in the previous-day market by bidding on sales and purchases. The sales and purchases… More >

Xiangjian Shi^1,*, Teng Liu², Wei Mu², Jianfeng Zhao¹

Energy Engineering, Vol.119, No.5, pp. 1843-1860, 2022, DOI:10.32604/ee.2022.020787

Abstract A microgrid (MG) refers to a set of loads, generation resources and energy storage systems acting as a controllable load or a generator to supply power and heating to a local area. The MG-generated power management is a central topic for MG design and operation. The existence of dispersed generation (DG) resources has faced MG management with new issues. Depending on the level of exchanges between an MG and the main grid, the MG operation states can be divided into independent or grid-connected ones. Energy management in MGs aims to supply power at the lowest cost for optimal load response.… More >

Daniyal M. Alghazzawi¹, Syed Hamid Hasan^1,*, Surbhi Bhatia²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3877-3897, 2022, DOI:10.32604/cmc.2022.024613

Abstract Detecting the anomalous entity in real-time network traffic is a popular area of research in recent times. Very few researches have focused on creating malware that fools the intrusion detection system and this paper focuses on this topic. We are using Deep Convolutional Generative Adversarial Networks (DCGAN) to trick the malware classifier to believe it is a normal entity. In this work, a new dataset is created to fool the Artificial Intelligence (AI) based malware detectors, and it consists of different types of attacks such as Denial of Service (DoS), scan 11, scan 44, botnet, spam, User Datagram Portal (UDP)… More >

Mohammed Hadwan^1,2,3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5545-5559, 2022, DOI:10.32604/cmc.2022.024512

Abstract A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in general have problems striking the… More >