Omar Almomani^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113

Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has two objectives; The first one… More >

Samer H. Atawneh¹, Waqar A. Khan², Nawaf N. Hamadneh^3,*, Adeeb M. Alhomoud³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 73-87, 2021, DOI:10.32604/cmc.2021.012351

Abstract The objectives of this study involve the optimization of longitudinal porous fins of square cross-section using metaheuristic algorithms. A generalized nonlinear ordinary differential equation is derived using Darcy and Fourier’s laws in the energy balance around a control volume and is solved numerically using RFK 45 method. The temperature of the base surface is higher than the fin surface, and the fin tip is kept adiabatic or cooled by convection heat transfer. The other pertinent parameters include Rayleigh number (100 ≤ Ra ≤ 10⁴), Darcy number, (10⁻⁴ ≤ Da ≤ 10⁻²), relative thermal conductivity ratio of solid phase to fluid (1000 ≤ k_r ≤ 8000), Nusselt number (10 ≤ Nu ≤ 100), porosity (0.1 ≤ φ ≤ 0.9).… More >

Sarab AlMuhaideb^*, Reem BinGhannam, Nourah Alhelal, Shatha Alduheshi, Fatimah Alkhamees, Raghad Alsuhaibani

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1329-1346, 2021, DOI:10.32604/cmc.2020.013576

Abstract Medical data classification (MDC) refers to the application of classification methods on medical datasets. This work focuses on applying a classification task to medical datasets related to specific diseases in order to predict the associated diagnosis or prognosis. To gain experts’ trust, the prediction and the reasoning behind it are equally important. Accordingly, we confine our research to learn rule-based models because they are transparent and comprehensible. One approach to MDC involves the use of metaheuristic (MH) algorithms. Here we report on the development and testing of a novel MH algorithm: IWD-Miner. This algorithm can be viewed as a fusion… More >

Viorel Minzu^*, Adrian Serbencu

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 663-677, 2020, DOI:10.32604/iasc.2020.010101

Abstract The idea for this work starts from the situation in which a metaheuristic-based algorithm has already been developed in order to solve an optimal control problem. This algorithm yields an offline "optimal" solution. On the other hand, the Receding Horizon Control (RHC) structure can be implemented if a process model is available. This work underlines some of the practical aspects of joining the RHC to an existing metaheuristic-based algorithm in order to obtain a closed-loop control structure that can be further used in real-time control. The result is a systematic procedure that integrates a given metaheuristic-based algorithm into a RHC… More >

Ahmed A. M. Jamel^1,∗, Bahriye Akay^2,†

Computer Systems Science and Engineering, Vol.34, No.5, pp. 259-281, 2019, DOI:10.32604/csse.2019.34.259

Abstract Parallel processing has turned into one of the emerging fields of machine learning due to providing consistent work by performing several tasks simultaneously, enhancing reliability (the presence of more than one device ensures the workflow even if some devices disrupted), saving processing time and introducing low cost and high-performance computation units. This research study presents a survey of parallel K-means and Fuzzy-c-means clustering algorithms based on their implementations in parallel environments such as Hadoop, MapReduce, Graphical Processing Units, and multi-core systems. Additionally, the enhancement in parallel clustering algorithms is investigated as hybrid approaches in which K-means and Fuzzy-c-means clustering algorithms… More >

Abeer I. Alhujaylan^{1, 2, *}, Manar I. Hosny¹

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1025-1051, 2020, DOI:10.32604/cmc.2020.08742

Abstract Mobile commerce (m-commerce) contributes to increasing the popularity of electronic commerce (e-commerce), allowing anybody to sell or buy goods using a mobile device or tablet anywhere and at any time. As demand for e-commerce increases tremendously, the pressure on delivery companies increases to organise their transportation plans to achieve profits and customer satisfaction. One important planning problem in this domain is the multi-vehicle profitable pickup and delivery problem (MVPPDP), where a selected set of pickup and delivery customers need to be served within certain allowed trip time. In this paper, we proposed hybrid clustering algorithms with the greedy randomised adaptive… More >

Lubna Alhenak¹, Manar Hosny^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1045-1074, 2019, DOI:10.32604/cmc.2019.08355

Abstract In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of a document in terms of… More >