Ming Li^1,*, Cairen Furifu¹, Chengyang Ge², Yunping Zheng¹, Shunfu Lin², Ronghui Liu²

Energy Engineering, Vol.120, No.8, pp. 1775-1801, 2023, DOI:10.32604/ee.2023.027215

Abstract As an effective carrier of integrated clean energy, the microgrid has attracted wide attention. The randomness of renewable energies such as wind and solar power output brings a significant cost and impact on the economics and reliability of microgrids. This paper proposes an optimization scheme based on the distributionally robust optimization (DRO) model for a microgrid considering solar-wind correlation. Firstly, scenarios of wind and solar power output scenarios are generated based on non-parametric kernel density estimation and the Frank-Copula function; then the generated scenario results are reduced by K-means clustering; finally, the probability confidence interval of scenario distribution is constrained… More >

Lei Shen^*, Ting Huang, Nishui Cai, Hao Wu

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 507-524, 2023, DOI:10.32604/iasc.2023.037640

Abstract Through the use of the internet and cloud computing, users may access their data as well as the programmes they have installed. It is now more challenging than ever before to choose which cloud service providers to take advantage of. When it comes to the dependability of the cloud infrastructure service, those who supply cloud services, as well as those who seek cloud services, have an equal responsibility to exercise utmost care. Because of this, further caution is required to ensure that the appropriate values are reached in light of the ever-increasing need for correct decision-making. The purpose of this… More >

P. Venkatesh^1,*, N. Visali²

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1001-1012, 2023, DOI:10.32604/iasc.2023.036268

Abstract In the conventional technique, in the evaluation of the severity index, clustering and loading suffer from more iteration leading to more computational delay. Hence this research article identifies, a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects. The polynomial load modelling or ZIP (constant impedances (Z), Constant Current (I) and Constant active power (P)) is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security. The process of finding the severity of the line using a Hybrid Line Stability Ranking Index (HLSRI) is used for… More >

Noor Ul Sabah¹, Muhammad Murad Khan^1,*, Ramzan Talib¹, Muhammad Anwar², Muhammad Sheraz Arshad Malik³, Puteri Nor Ellyza Nohuddin⁴

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4955-4972, 2023, DOI:10.32604/cmc.2023.037436

Abstract Education quality has undoubtedly become an important local and international benchmark for education, and an institute’s ranking is assessed based on the quality of education, research projects, theses, and dissertations, which has always been controversial. Hence, this research paper is influenced by the institutes ranking all over the world. The data of institutes are obtained through Google Scholar (GS), as input to investigate the United Kingdom’s Research Excellence Framework (UK-REF) process. For this purpose, the current research used a Bespoke Program to evaluate the institutes’ ranking based on their source. The bespoke program requires changes to improve the results by… More >

Tayyaba Noreen^1,*, Qiufen Xia¹, Muhammad Zeeshan Haider²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2593-2613, 2023, DOI:10.32604/cmc.2023.036139

Abstract In the past decade, blockchain has evolved as a promising solution to develop secure distributed ledgers and has gained massive attention. However, current blockchain systems face the problems of limited throughput, poor scalability, and high latency. Due to the failure of consensus algorithms in managing nodes’identities, blockchain technology is considered inappropriate for many applications, e.g., in IoT environments, because of poor scalability. This paper proposes a blockchain consensus mechanism called the Advanced DAG-based Ranking (ADR) protocol to improve blockchain scalability and throughput. The ADR protocol uses the directed acyclic graph ledger, where nodes are placed according to their ranking positions… More >

Weijun Li¹, Xin Die², Zhicheng Ma³, Jinping Zhang³, Haiying Dong^1,*

Energy Engineering, Vol.120, No.4, pp. 1001-1022, 2023, DOI:10.32604/ee.2023.024426

Abstract Aiming at the problems of large-scale wind and solar grid connection, how to ensure the economy of system operation and how to realize fair scheduling between new energy power stations, a two-stage optimal dispatching model of wind power-photovoltaic-solar thermal combined system considering economic optimality and fairness is proposed. Firstly, the first stage dispatching model takes the overall economy optimization of the system as the goal and the principle of maximizing the consumption of wind and solar output, obtains the optimal output value under the economic conditions of each new energy station, and then obtains the maximum consumption space of the… More > Graphic Abstract

Qiuying Shen¹, Wentao Zhang¹, Mofei Song^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 197-217, 2023, DOI:10.32604/cmc.2023.036365

Abstract With the rapid development of the internet of things (IoT), electricity consumption data can be captured and recorded in the IoT cloud center. This provides a credible data source for enterprise credit scoring, which is one of the most vital elements during the financial decision-making process. Accordingly, this paper proposes to use deep learning to train an enterprise credit scoring model by inputting the electricity consumption data. Instead of predicting the credit rating, our method can generate an absolute credit score by a novel deep ranking model–ranking extreme gradient boosting net (rankXGB). To boost the performance, the rankXGB model combines… More >

Vladimir Poplygin^1,*, Chengzhi Qi², Mikhail Guzev³, Evgenii Kozhevnikov¹, Artem Kunitskikh¹, Evgenii Riabokon¹, Mikhail Turbakov¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1495-1505, 2023, DOI:10.32604/fdmp.2023.022335

Abstract A set of techniques for well treatment aimed to enhance oil recovery are considered in the present study. These are based on the application of elastic waves of various types (dilation-wave, vibro-wave, or other acoustically induced effects). In such a context, a new technique is proposed to predict the effectiveness of the elastic-wave well treatment using the rank distribution according to Zipf’s law. It is revealed that, when the results of elastic wave well treatments are analyzed, groups of wells exploiting various geological deposits can differ in terms of their slope coefficients and free members. As the slope coefficient increases,… More >

Da Li, Guodong Zhang, Ke Sun^*, Shuzhan Bai, Guoxiang Li^*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1479-1493, 2023, DOI:10.32604/fdmp.2023.022634

Abstract A dedicated heat exchanger model is introduced for the optimization of heavy-duty diesel engines. The model is a prerequisite for the execution of CFD simulations, which are used to improve waste heat recovery in these systems. Several optimization methods coupled with different types of working fluids are compared in terms of exergy efficiency and heat exchanger complicity. The three considered optimization methods all lead to significant improvements in the R245fa and R1233zd systems with a comparatively low evaporation temperature. The optimal R245fa system has the highest efficiency increase (77.49%). The cyclopentane system displays the highest effi- ciency among the optimized… More >

A. Thiruppathi^*, C. K. Kirubhashankar

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2253-2266, 2023, DOI:10.32604/iasc.2023.033870

Abstract The output of the fuzzy set is reduced by one for the defuzzification procedure. It is employed to provide a comprehensible outcome from a fuzzy inference process. This page provides further information about the defuzzification approach for quadrilateral fuzzy numbers, which may be used to convert them into discrete values. Defuzzification demonstrates how useful fuzzy ranking systems can be. Our major purpose is to develop a new ranking method for generalized quadrilateral fuzzy numbers. The primary objective of the research is to provide a novel approach to the accurate evaluation of various kinds of fuzzy integers. Fuzzy ranking properties are… More >