Christophe Chesneau^1,*, Hassan Doosti²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 981-983, 2023, DOI:10.32604/cmes.2023.028283

Abstract This article has no abstract. More >

Suthep Suantai^1,2, Zulqurnain Sabir^3,4, Muhammad Asif Zahoor Raja⁵, Watcharaporn Cholamjiak^6,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2155-2170, 2023, DOI:10.32604/cmc.2023.034699

Abstract The purpose of this study is to present the numerical performances and interpretations of the SEIR nonlinear system based on the Zika virus spreading by using the stochastic neural networks based intelligent computing solver. The epidemic form of the nonlinear system represents the four dynamics of the patients, susceptible patients S(y), exposed patients hospitalized in hospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIR model. The computing numerical outcomes and performances of the system are examined by using the artificial neural networks (ANNs) and the scaled conjugate gradient (SCG) for the training of the networks, i.e., ANNs-SCG. The… More >

Xingquan Zhang¹, Renjun Xie¹, Kuan Liu^2,*, Yating Li², Yuqiang Xu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1721-1733, 2023, DOI:10.32604/fdmp.2023.025578

Abstract The well-known “lost circulation” problem refers to the uncontrolled flow of whole mud into a formation. In order to address the problem related to the paucity of available data, in the present study, a model is introduced for the lost-circulation risk sample profile of a drilled well. The model is built taking into account effective data (the Block L). Then, using a three-dimensional geological modeling software, relying on the variation function and sequential Gaussian simulation method, a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses. More >

Li Yan¹, Zulqurnain Sabir², Esin Ilhan³, Muhammad Asif Zahoor Raja⁴, Wei Gao⁵, Haci Mehmet Baskonus^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094

Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and precise frameworks to tackle stiff… More >

V. Saikumari^*, V. Sunitha

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1797-1810, 2023, DOI:10.32604/iasc.2023.034038

Abstract Recently, gender equality and women’s entrepreneurship have gained considerable attention in global economic development. Prior to the design of any policy interventions to increase women’s entrepreneurship, it is significant to comprehend the factors motivating women to become entrepreneurs. The non-understanding of the factors can result in the endurance of low living standards and the design of expensive and ineffectual policies. But female involvement in entrepreneurship becomes higher in developing economies compared to developed economies. Women Entrepreneurship Index (WEI) plays a vital role in determining the factors that enable the flourishment of high potential female entrepreneurs which enhances economic welfare and… More >

Ibrahim M. Almanjahie^1,2,*, Omar Fetitah³, Mohammed Kadi Attouch³, Tawfik Benchikh^3,4

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6307-6319, 2023, DOI:10.32604/cmc.2023.033441

Abstract Functional statistics is a new technique for dealing with data that can be viewed as curves or images. Parallel to this approach, the Near-Infrared Reflectance (NIR) spectroscopy methodology has been used in modern chemistry as a rapid, low-cost, and exact means of assessing an object’s chemical properties. In this research, we investigate the quality of corn and cookie dough by analyzing the spectroscopic technique using certain cutting-edge statistical models. By analyzing spectral data and applying functional models to it, we could predict the chemical components of corn and cookie dough. Kernel Functional Classical Estimation (KFCE), Kernel Functional Quantile Estimation (KFQE),… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Mazen Nassar^2,4, Ahmed Elshahhat^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2065-2089, 2023, DOI:10.32604/cmes.2023.023408

Abstract This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique. We refer to the new model as modified alpha power transformed Weibull distribution. The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions, which are quite familiar in environmental investigations. Its hazard rate function can be decreasing, increasing, bathtub and upside-down then bathtub shaped. Diverse structural properties of the proposed model are acquired including quantile function, moments, entropies, order statistics, residual life and reversed failure… More >

Refah Alotaibi¹, Hassan Okasha^2,3, Hoda Rezk⁴, Mazen Nassar^2,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1255-1274, 2023, DOI:10.32604/cmes.2022.022623

Abstract The objective of this article is to provide a novel extension of the conventional inverse Weibull distribution that adds an extra shape parameter to increase its flexibility. This addition is beneficial in a variety of fields, including reliability, economics, engineering, biomedical science, biological research, environmental studies, and finance. For modeling real data, several expanded classes of distributions have been established. The modified alpha power transformed approach is used to implement the new model. The data matches the new inverse Weibull distribution better than the inverse Weibull distribution and several other competing models. It appears to be a distribution designed to… More >

S. Vanitha^1,*, P. Balasubramanie²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 849-864, 2023, DOI:10.32604/iasc.2023.032324

Abstract Internet of things (IOT) possess cultural, commercial and social effect in life in the future. The nodes which are participating in IOT network are basically attracted by the cyber-attack targets. Attack and identification of anomalies in IoT infrastructure is a growing problem in the IoT domain. Machine Learning Based Ensemble Intrusion Detection (MLEID) method is applied in order to resolve the drawback by minimizing malicious actions in related botnet attacks on Message Queue Telemetry Transport (MQTT) and Hyper-Text Transfer Protocol (HTTP) protocols. The proposed work has two significant contributions which are a selection of features and detection of attacks. New… More >

Sakthiseswari Ganasan¹, You Huay Woon^2,*, Zainol Mustafa¹, Dadasaheb G. Godase³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1-10, 2023, DOI:10.32604/iasc.2023.032062

Abstract A memory-type control chart utilizes previous information for chart construction. An example of a memory-type chart is an exponentially-weighted moving average (EWMA) control chart. The EWMA control chart is well-known and widely employed by practitioners for monitoring small and moderate process mean shifts. Meanwhile, the EWMA median chart is robust against outliers. In light of this, the economic model of the EWMA and EWMA median control charts are commonly considered. This study aims to investigate the effect of cost parameters on the out-of-control average run length in implementing EWMA and EWMA median control charts. The economic model was used to… More >