Lingai Guo¹, Marwan Fahs², Hussein Hoteit³, Rui Gao^1,*, Qian Shao^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 279-297, 2021, DOI:10.32604/cmes.2021.016619

Abstract Numerical modeling of seepage-induced consolidation process usually encounters significant uncertainty in the properties of geotechnical materials. Assessing the effect of uncertain parameters on the performance variability of the seepage consolidation model is of critical importance to the simulation and tests of this process. To this end, the uncertainty and sensitivity analyses are performed on a seepage consolidation model in a fractured porous medium using the Bayesian sparse polynomial chaos expansion (SPCE) method. Five uncertain parameters including Young’s modulus, Poisson’s ratio, and the permeability of the porous matrix, the permeability within the fracture, and Biot’s constant are studied. Bayesian SPCE models… More >

Zhenzhen Zhang¹, Kai Lan^2,*

Journal of Renewable Materials, Vol.10, No.1, pp. 53-73, 2022, DOI:10.32604/jrm.2022.017506

Abstract Understanding the economic feasibility of cross-laminated timber (CLT), an emerging and sustainable alternative to concrete and steel, is critical for the rapid expansion of the mass timber industry. However, previous studies on economic performance of CLT have not fully considered the variations in the feedstock, plant capacities, manufacturing parameters, and capital and operating costs. This study fills this gap by developing a techno-economic analysis of producing CLT panels in the Southern United States. The effects of those variations on minimum selling price (MSP) of CLT panels are explored by Monte Carlo simulation. The results show that, across all the plant… More >

Hussein Abdel-Mawgoud¹, Salah Kamel¹, Hegazy Rezk^2,3, Tahir Khurshaid⁴, Sang-Bong Rhee^4,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1463-1481, 2021, DOI:10.32604/cmc.2021.017995

Abstract Recently, implementation of Battery Energy Storage (BES) with photovoltaic (PV) array in distribution networks is becoming very popular in overall the world. Integrating PV alone in distribution networks generates variable output power during 24-hours as it depends on variable natural source. PV can be able to generate constant output power during 24-hours by installing BES with it. Therefore, this paper presents a new application of a recent metaheuristic algorithm, called Slime Mould Algorithm (SMA), to determine the best size, and location of photovoltaic alone or with battery energy storage in the radial distribution system (RDS). This algorithm is modeled from… More >

Oakyoung Han¹, Jaehyoun Kim^2,*

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

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 Electric Power Corporation using robotic… 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

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 method (henceforth referred to as… 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

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 importance of the selected criteria… 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

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 deterministic dynamic systems, without changing… 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

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 the photo-voltaic system.… 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

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

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 divide the original dataset and… More >