Oakyoung Han¹, Jaehyoun Kim^2,*

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2621-2632, 2021, DOI:10.32604/cmc.2021.014665 - 13 April 2021

Abstract The analysis of large time-series datasets has profoundly enhanced our ability to make accurate predictions in many fields. However, unpredictable phenomena, such as extreme weather events or the novel coronavirus 2019 (COVID-19) outbreak, can greatly limit the ability of time-series analyses to establish reliable patterns. The present work addresses this issue by applying uncertainty analysis using a probability distribution function, and applies the proposed scheme within a preliminary study involving the prediction of power consumption for a single hotel in Seoul, South Korea based on an analysis of 53,567 data items collected by the Korea… More >

Vin Cent Tai^1,*, Yong Chai Tan¹, Nor Faiza Abd Rahman¹, Hui Xin Che², Chee Ming Chia², Lip Huat Saw³, Mohd Fozi Ali⁴

Energy Engineering, Vol.118, No.3, pp. 715-725, 2021, DOI:10.32604/EE.2021.014865 - 22 March 2021

Abstract Electricity demand is also known as load in electric power system. This article presents a Long-Term Load Forecasting (LTLF) approach for Malaysia. An Artificial Neural Network (ANN) of 5-layer Multi-Layered Perceptron (MLP) structure has been designed and tested for this purpose. Uncertainties of input variables and ANN model were introduced to obtain the prediction for years 2022 to 2030. Pearson correlation was used to examine the input variables for model construction. The analysis indicates that Primary Energy Supply (PES), population, Gross Domestic Product (GDP) and temperature are strongly correlated. The forecast results by the proposed… More >

Mohamed Abdel-Basset¹, Rehab Mohamed¹, Mohamed Elhoseny², Mohamed Abouhawash^2,3, Yunyoung Nam^4,*, Nabil M. AbdelAziz¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2729-2746, 2021, DOI:10.32604/cmc.2021.015316 - 01 March 2021

Abstract Evaluation of commercial banks (CBs) performance has been a significant issue in the financial world and deemed as a multi-criteria decision making (MCDM) model. Numerous research assesses CB performance according to different metrics and standers. As a result of uncertainty in decision-making problems and large economic variations in Egypt, this research proposes a plithogenic based model to evaluate Egyptian commercial banks’ performance based on a set of criteria. The proposed model evaluates the top ten Egyptian commercial banks based on three main metrics including financial, customer satisfaction, and qualitative evaluation, and 19 sub-criteria. The proportional… More >

Liqun Wang¹, Zengtao Chen², Guolai Yang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 479-503, 2021, DOI:10.32604/cmes.2021.011954 - 21 January 2021

Abstract This paper proposes a non-intrusive uncertainty analysis method for artillery dynamics involving hybrid uncertainty using polynomial chaos expansion (PCE). The uncertainty parameters with sufficient information are regarded as stochastic variables, whereas the interval variables are used to treat the uncertainty parameters with limited stochastic knowledge. In this method, the PCE model is constructed through the Galerkin projection method, in which the sparse grid strategy is used to generate the integral points and the corresponding integral weights. Through the sampling in PCE, the original dynamic systems with hybrid stochastic and interval parameters can be transformed into… More >

D. Menaga¹, M. Premkumar², R. Sowmya^1,*, S. Narasimman³

Energy Engineering, Vol.117, No.6, pp. 481-495, 2020, DOI:10.32604/EE.2020.013282 - 16 October 2020

Abstract The proposed controller accompanies with different sliding surfaces. To understand maximum power point extraction as opposed to nonlinear uncertainties and unknown disturbance of a grid-connected photovoltaic system to various control inputs (u_d, u_q) is designed. To extract maximum power from a solar array and maintain unity power flow in a grid by controlling the voltage across the dclink capacitor (V_pvdc) and reactive current (i_q). A multiple input-output with multiple uncertainty constraints have considered designing proposed sliding mode controllers to validated their robustness performance. An innovative controller verifies uncertain inputs, constant and changes in irradiances, and temperature of More >

Fan Yang^1,2,3,*, Jianwei Ren^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 801-814, 2020, DOI:10.32604/cmes.2020.08889 - 12 October 2020

Abstract Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. More >

Xing Deng^1,2, Haijian Shao^1,2,*, Xia Wang^3,4

Energy Engineering, Vol.117, No.5, pp. 289-299, 2020, DOI:10.32604/EE.2020.011126 - 07 September 2020

Abstract Wind speed’s distribution nature such as uncertainty and randomness imposes a challenge in high accuracy forecasting. Based on the energy distribution about the extracted amplitude and associated frequency, the uncertainty measurement is processed through Rényi entropy analysis method with time-frequency nature. Nonparametric statistical method is used to test the randomness of wind speed, more precisely, whether or not the wind speed time series is independent and identically distribution (i.i.d) based on the output probability. Seasonal characteristics of wind speed are analyzed based on self-similarity in periodogram under scales range generated by wavelet transformation to reasonably More >

S.Ilangovan^1,*, A. Vincent Antony Kumar²

Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 261-268, 2020, DOI:10.31209/2019.100000154

Abstract In this work, a Novel Feature selection framework called SU embedded PSO Feature Selector has been proposed (SU-PSO) towards the selection of optimal feature subset for the improvement of detection performance of classifiers. The feature space ranking is done through the Symmetrical Uncertainty method. Further, memetic operators of PSO include features and remove features are used to choose relevant features and the best of best features are selected using PSO. The proposed feature selector efficiently removes not only irrelevant but also redundant features. Performance metric such as classification accuracy, subset of features selected and running More >

Tairan Hu¹, Tianyang Zhou¹, Yichao Zang^{1, *}, Qingxian Wang¹, Hang Li²

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1795-1807, 2020, DOI:10.32604/cmc.2020.011071 - 20 August 2020

Abstract With serious cybersecurity situations and frequent network attacks, the demands for automated pentests continue to increase, and the key issue lies in attack planning. Considering the limited viewpoint of the attacker, attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach, but it also poses some challenges. To address the efficiency problem in uncertainty planning, we propose the APU-D* Lite algorithm in this paper. First, the pentest framework is mapped to the planning problem with the Planning Domain Definition Language (PDDL). Next, we develop the pentest information graph… More >

Nan Wu^1,#, Kuan Lu^1,2,#,*, Yulin Jin^2,3,*, Haopeng Zhang¹, Yushu Chen²

Sound & Vibration, Vol.54, No.2, pp. 113-125, 2020, DOI:10.32604/sv.2020.09783 - 09 May 2020

Abstract Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional decomposition (PDD) method is applied to the 2 DOFs spring system considering the uncertain stiffness to study the More >