Qasem Al-Tashi^1,*, Tareq M Shami², Said Jadid Abdulkadir³, Emelia Akashah Patah Akhir³, Ayed Alwadain⁴, Hitham Alhussain³, Alawi Alqushaibi³, Helmi MD Rais³, Amgad Muneer¹, Maliazurina B. Saad¹, Jia Wu¹, Seyedali Mirjalili^5,6,7,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1937-1966, 2023, DOI:10.32604/csse.2023.039788 - 28 July 2023

Abstract The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized. While it is a multi-objective problem, current methods tend to treat feature selection as a single-objective optimization task. This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase (LMuMOGWO) for tackling feature selection problems. The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer (MOGWO): a Lévy flight and a mutation operator. The Lévy flight, a type of… More >

K. S. Bhuvaneshwari¹, Ahmed Najat Ahmed², Mehedi Masud³, Samah H. Alajmani⁴, Mohamed Abouhawwash^5,6,*

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2933-2945, 2023, DOI:10.32604/csse.2023.034288 - 03 April 2023

Abstract The immediate and quick spread of the coronavirus has become a life-threatening disease around the globe. The widespread illness has dramatically changed almost all sectors, moving from offline to online, resulting in a new normal lifestyle for people. The impact of coronavirus is tremendous in the healthcare sector, which has experienced a decline in the first quarter of 2020. This pandemic has created an urge to use computer-aided diagnosis techniques for classifying the Covid-19 dataset to reduce the burden of clinical results. The current situation motivated me to choose correlation-based development called correlation-based grey wolf… More >

Fatih Ahmet Şenel^*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4587-4600, 2023, DOI:10.32604/cmc.2023.033155 - 31 October 2022

Abstract In this study, the morphological galaxy classification process was carried out with a hybrid approach. Since the Galaxy classification process may contain detailed information about the universe’s formation, it remains the current research topic. Researchers divided more than 100 billion galaxies into ten different classes. It is not always possible to understand which class the galaxy types belong. However, Artificial Intelligence (AI) can be used for successful classification. There are studies on the automatic classification of galaxies into a small number of classes. As the number of classes increases, the success of the used methods… More >

T. Thanya^1,*, S. Wilfred Franklin²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 97-112, 2023, DOI:10.32604/iasc.2023.029675 - 29 September 2022

Abstract At an early point, the diagnosis of pancreatic cancer is mediocre, since the radiologist is skill deficient. Serious threats have been posed due to the above reasons, hence became mandatory for the need of skilled technicians. However, it also became a time-consuming process. Hence the need for automated diagnosis became mandatory. In order to identify the tumor accurately, this research proposes a novel Convolution Neural Network (CNN) based superior image classification technique. The proposed deep learning classification strategy has a precision of 97.7%, allowing for more effective usage of the automatically executed feature extraction technique More >

Hatim G. Zaini^*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2303-2314, 2022, DOI:10.32604/cmc.2022.021998 - 07 December 2021

Abstract This paper gives and analyses data-driven prediction models for the energy usage of appliances. Data utilized include readings of temperature and humidity sensors from a wireless network. The building envelope is meant to minimize energy demand or the energy required to power the house independent of the appliance and mechanical system efficiency. Approximating a mapping function between the input variables and the continuous output variable is the work of regression. The paper discusses the forecasting framework FOPF (Feature Optimization Prediction Framework), which includes feature selection optimization: by removing non-predictive parameters to choose the best-selected feature More >

M. Premkumar¹, Pradeep Jangir², B. Santhosh Kumar³, Mohammad A. Alqudah⁴, Kottakkaran Sooppy Nisar^5,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2435-2452, 2022, DOI:10.32604/cmc.2022.016488 - 27 September 2021

Abstract The first step in the design phase of the Brushless Direct Current (BLDC) motor is the formulation of the mathematical framework and is often used due to its analytical structure. Therefore, the BLDC motor design problem is considered to be an optimization problem. In this paper, the analytical model of the BLDC motor is presented, and it is considered to be a basis for emphasizing the optimization methods. The analytical model used for the experimentation has 78 non-linear equations, two objective functions, five design variables, and six non-linear constraints, so the BLDC motor design problem… More >

Gagandeep Singh Walia¹, Parulpreet Singh¹, Manwinder Singh¹, Mohamed Abouhawwash^2,3, Hyung Ju Park⁴, Byeong-Gwon Kang^4,*, Shubham Mahajan⁵, Amit Kant Pandit⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 305-321, 2022, DOI:10.32604/cmc.2022.019171 - 07 September 2021

Abstract Location information plays an important role in most of the applications in Wireless Sensor Network (WSN). Recently, many localization techniques have been proposed, while most of these deals with two Dimensional applications. Whereas, in Three Dimensional applications the task is complex and there are large variations in the altitude levels. In these 3D environments, the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level. For such applications, 2D localization models are not reliable. Due to this, the design of 3D localization systems in WSNs faces new challenges. In this… More >

El-Sayed M. El-kenawy¹, Hattan F. Abutarboush², Ali Wagdy Mohamed^3,4, Abdelhameed Ibrahim^5,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2983-2995, 2021, DOI:10.32604/cmc.2021.019114 - 24 August 2021

Abstract Machine learning (ML) has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design strolls. ML is a massive area within artificial intelligence (AI) that focuses on obtaining valuable information out of data, explaining why ML has often been related to stats and data science. An advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture design. The algorithm is designed, depending on the hybrid between the Sine Cosine Algorithm (SCA) and the Grey Wolf Optimizer More >

Adel Hamdan Mohammad^*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 65-80, 2021, DOI:10.32604/iasc.2021.016140 - 26 July 2021

Abstract Intrusion detection is an important topic that aims at protecting computer systems. Besides, feature selection is crucial for increasing the performance of intrusion detection. This paper employs a new hybrid feature selection model for intrusion detection. The implemented model uses Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms in a new manner. In addition, this study introduces two new models called (PSO-GWO-NB) and (PSO-GWO-ANN) for feature selection and intrusion detection. PSO and GWO show emergent results in feature selection for several purposes and applications. This paper uses PSO and GWO to select features… More >

A. M. Abdullah¹, Hegazy Rezk^2,3,*, Abdelrahman Elbloye¹, Mohamed K. Hassan^1,4, A. F. Mohamed^1,5

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 729-740, 2021, DOI:10.32604/iasc.2021.018595 - 01 July 2021

Abstract The energy harvested from a thermoelectric generator (TEG) relies mostly on the difference in temperature between the hot side and cold side of the TEG along with the connected load. Hence, a reliable maximum power point tracker is needed to force the TEG to operate close to the maximum power point (MPP) with any variation during the operation. In the current work, an optimized fractional maximum power point tracker (OFMPPT) is proposed to improve the performance of the TEG. The proposed tracker is based on fractional control. The optimal parameters of the OFMPPT have been… More >