El-Sayed M. El-kenawy^1,2, Abdelhameed Ibrahim^3,*, Seyedali Mirjalili^4,5, Yu-Dong Zhang⁶, Shaima Elnazer^7,8, Rokaia M. Zaki^9,10

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884

Abstract Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of the Metamaterial Antenna. Support Vector… More >

Punit Gupta¹, Sanjit Bhagat², Dinesh Kumar Saini^1,*, Ashish Kumar², Mohammad Alahmadi³, Prakash Chandra Sharma¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5659-5676, 2022, DOI:10.32604/cmc.2022.023056

Abstract In the next generation of computing environment e-health care services depend on cloud services. The Cloud computing environment provides a real-time computing environment for e-health care applications. But these services generate a huge number of computational tasks, real-time computing and comes with a deadline, so conventional cloud optimization models cannot fulfil the task in the least time and within the deadline. To overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization with the least simulation time. In order… More >

Ayman Altameem¹, Sandeep Kumar², Ramesh Chandra Poonia³, Abdul Khader Jilani Saudagar^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177

Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.… More >

Mesfer Al Duhayyim¹, Radwa Marzouk^2,3, Fahd N. Al-Wesabi⁴, Maram Alrajhi⁵, Manar Ahmed Hamza^6,*, Abu Sarwar Zamani⁶

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1233-1247, 2022, DOI:10.32604/cmc.2022.021652

Abstract Recent advancements in computer technologies for data processing, collection, and storage have offered several chances to improve the abilities in production, services, communication, and researches. Data mining (DM) is an interdisciplinary field commonly used to extract useful patterns from the data. At the same time, educational data mining (EDM) is a kind of DM concept, which finds use in educational sector. Recently, artificial intelligence (AI) techniques can be used for mining a large amount of data. At the same time, in DM, the feature selection process becomes necessary to generate subset of features and can be solved by the use… More >

Mustafa Abdul Salam^1,*, Ahmad Taher Azar², Rana Hussien²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6339-6363, 2022, DOI:10.32604/cmc.2022.020583

Abstract Extreme Learning Machine (ELM) is popular in batch learning, sequential learning, and progressive learning, due to its speed, easy integration, and generalization ability. While, Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence, high time and space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there is no certainty that the arrangement of weights and biases within the hidden layer is optimal. To solve this problem, the traditional ELM has been hybridized with swarm intelligence optimization techniques. This paper displays five proposed hybrid Algorithms “Salp Swarm Algorithm (SSA-ELM), Grasshopper… More >

Moatasem M. Draz¹, Marwa S. Farhan^2,3,*, Sarah N. Abdulkader^4,5, M. G. Gafar^6,7

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1919-1935, 2021, DOI:10.32604/cmc.2021.015586

Abstract Software systems have been employed in many fields as a means to reduce human efforts; consequently, stakeholders are interested in more updates of their capabilities. Code smells arise as one of the obstacles in the software industry. They are characteristics of software source code that indicate a deeper problem in design. These smells appear not only in the design but also in software implementation. Code smells introduce bugs, affect software maintainability, and lead to higher maintenance costs. Uncovering code smells can be formulated as an optimization problem of finding the best detection rules. Although researchers have recommended different techniques to… More >

Sally M. Elghamrawy¹, Aboul Ella Hassnien^2,*, Vaclav Snasel³

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2353-2371, 2021, DOI:10.32604/cmc.2021.014767

Abstract Detecting COVID-19 cases as early as possible became a critical issue that must be addressed to avoid the pandemic’s additional spread and early provide the appropriate treatment to the affected patients. This study aimed to develop a COVID-19 diagnosis and prediction (AIMDP) model that could identify patients with COVID-19 and distinguish it from other viral pneumonia signs detected in chest computed tomography (CT) scans. The proposed system uses convolutional neural networks (CNNs) as a deep learning technology to process hundreds of CT chest scan images and speeds up COVID-19 case prediction to facilitate its containment. We employed the whale optimization… More >

Wenyan Guo^{1, *}, Ting Liu¹, Fang Dai¹, Peng Xu¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06411

Abstract Whale optimization algorithm (WOA) is a new population-based metaheuristic algorithm. WOA uses shrinking encircling mechanism, spiral rise, and random learning strategies to update whale’s positions. WOA has merit in terms of simple calculation and high computational accuracy, but its convergence speed is slow and it is easy to fall into the local optimal solution. In order to overcome the shortcomings, this paper integrates adaptive neighborhood and hybrid mutation strategies into whale optimization algorithms, designs the average distance from itself to other whales as an adaptive neighborhood radius, and chooses to learn from the optimal solution in the neighborhood instead of… More >