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 - 23 March 2022

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 More >

El-Sayed M. El-Kenawy^1,2, Abdelhameed Ibrahim³, Nadjem Bailek^4,*, Kada Bouchouicha⁵, Muhammed A. Hassan⁶, Basharat Jamil⁷, Nadhir Al-Ansari⁸

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5837-5854, 2022, DOI:10.32604/cmc.2022.023257 - 14 January 2022

Abstract In order to achieve a highly accurate estimation of solar energy resource potential, a novel hybrid ensemble-learning approach, hybridizing Advanced Squirrel-Search Optimization Algorithm (ASSOA) and support vector regression, is utilized to estimate the hourly tilted solar irradiation for selected arid regions in Algeria. Long-term measured meteorological data, including mean-air temperature, relative humidity, wind speed, alongside global horizontal irradiation and extra-terrestrial horizontal irradiance, were obtained for the two cities of Tamanrasset-and-Adrar for two years. Five computational algorithms were considered and analyzed for the suitability of estimation. Further two new algorithms, namely Average Ensemble and Ensemble using… More >

Tanzila Saba¹, Mirza Naveed Shahzad^2,*, Sonia Iqbal^2,3, Amjad Rehman¹, Ibrahim Abunadi¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4785-4801, 2022, DOI:10.32604/cmc.2022.022309 - 14 January 2022

Abstract Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In… More >

N. Ashwini^1,*, V. Nagaveni², Manoj Kumar Singh³

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 893-908, 2022, DOI:10.32604/iasc.2022.022231 - 17 November 2021

Abstract Forecasting for a time series signal carrying single pattern characteristics can be done properly using function mapping-based principle by a well-designed artificial neural network model. But the performances degraded very much when time series carried the mixture of different patterns characteristics. The level of difficulty increases further when there is a need to predict far time samples. Among several possible mixtures of patterns, the trend-cycle time series is having its importance because of its occurrence in many real-life applications like in electric power generation, fuel consumption and automobile sales. Over the mixed characteristics of patterns,… More >

P. Rajeswari^*, K. Jayashree

Computer Systems Science and Engineering, Vol.41, No.2, pp. 511-524, 2022, DOI:10.32604/csse.2022.020352 - 25 October 2021

Abstract Recent advancements in cloud computing (CC) technologies signified that several distinct web services are presently developed and exist at the cloud data centre. Currently, web service composition gains maximum attention among researchers due to its significance in real-time applications. Quality of Service (QoS) aware service composition concerned regarding the election of candidate services with the maximization of the whole QoS. But these models have failed to handle the uncertainties of QoS. The resulting QoS of composite service identified by the clients become unstable and subject to risks of failing composition by end-users. On the other… More >

Amgad Muneer^1,2,*, Shakirah Mohd Taib^1,2, Suliman Mohamed Fati³, Abdullateef O. Balogun¹, Izzatdin Abdul Aziz^1,2

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5363-5381, 2022, DOI:10.32604/cmc.2022.021113 - 11 October 2021

Abstract Anomaly detection in high dimensional data is a critical research issue with serious implication in the real-world problems. Many issues in this field still unsolved, so several modern anomaly detection methods struggle to maintain adequate accuracy due to the highly descriptive nature of big data. Such a phenomenon is referred to as the “curse of dimensionality” that affects traditional techniques in terms of both accuracy and performance. Thus, this research proposed a hybrid model based on Deep Autoencoder Neural Network (DANN) with five layers to reduce the difference between the input and output. The proposed… More >

Samar Nour^1,*, Sameh A. Salem^1,2, Shahira M. Habashy¹

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4447-4466, 2022, DOI:10.32604/cmc.2022.020775 - 11 October 2021

Abstract Recently, Multicore systems use Dynamic Voltage/Frequency Scaling (DV/FS) technology to allow the cores to operate with various voltage and/or frequencies than other cores to save power and enhance the performance. In this paper, an effective and reliable hybrid model to reduce the energy and makespan in multicore systems is proposed. The proposed hybrid model enhances and integrates the greedy approach with dynamic programming to achieve optimal Voltage/Frequency (Vmin/F) levels. Then, the allocation process is applied based on the available workloads. The hybrid model consists of three stages. The first stage gets the optimum safe voltage More >

Mohammad Hadwan^1,2,3,*, Basheer M. Al-Maqaleh⁴ , Fuad N. Al-Badani⁵ , Rehan Ullah Khan^1,3, Mohammed A. Al-Hagery⁶

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4829-4845, 2022, DOI:10.32604/cmc.2022.017824 - 11 October 2021

Abstract

Time series forecasting plays a significant role in numerous applications, including but not limited to, industrial planning, water consumption, medical domains, exchange rates and consumer price index. The main problem is insufficient forecasting accuracy. The present study proposes a hybrid forecasting methods to address this need. The proposed method includes three models. The first model is based on the autoregressive integrated moving average (ARIMA) statistical model; the second model is a back propagation neural network (BPNN) with adaptive slope and momentum parameters; and the third model is a hybridization between ARIMA and BPNN (ARIMA/BPNN) and artificial

… More >

Xiyang Li^1,2, Bin Cheng^1,2, Hui Zhang^1,2,*, Xianghan Zhang¹, Zhi Yun¹

Energy Engineering, Vol.118, No.6, pp. 1869-1886, 2021, DOI:10.32604/EE.2021.015542 - 10 September 2021

Abstract With the continuous increase in the proportional use of wind energy across the globe, the reduction of power generation efficiency and safety hazards caused by the icing on wind turbine blades have attracted more consideration for research. Therefore, it is crucial to accurately analyze the thickness of icing on wind turbine blades, which can serve as a basis for formulating corresponding control measures and ensure a safe and stable operation of wind turbines in winter times and/or in high altitude areas. This paper fully utilized the advantages of the support vector machine (SVM) and back-propagation More >

Omar Almomani^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113 - 22 March 2021

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… More >