Amina Mahreen¹, Fateh Mebarek-Oudina^2,3,4,*, Amna Ashfaq¹, Jawad Raza¹, Sami Ullah Khan⁵, Hanumesh Vaidya⁶

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2829-2853, 2025, DOI:10.32604/fdmp.2025.072492 - 01 December 2025

Abstract Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems. This study investigates the magnetohydrodynamic (MHD) thermosolutal convection of a Casson fluid within an inclined, porous microchannel subjected to convective boundary conditions. The nonlinear, coupled equations governing momentum, energy, and species transport are solved numerically using the MATLAB bvp4c solver, ensuring high numerical accuracy and stability. To identify the dominant parameters influencing flow behavior and to optimize transport performance, a comprehensive hybrid optimization framework—combining a modified Taguchi design, Grey… More >

Mingchen Gao^*

Energy Engineering, Vol.122, No.8, pp. 3243-3263, 2025, DOI:10.32604/ee.2025.065957 - 24 July 2025

Abstract Currently, the international economic situation is becoming increasingly complex, and there is significant downward pressure on the global economy. In recent years, China’s infrastructure sector has experienced rapid growth, with the structure of its power engineering business gradually shifting from traditional infrastructure construction to more diversified areas such as production and operation, as well as emergency repairs. As a result, the transformation of mechanized construction in power transmission and transformation projects has become increasingly urgent. This article proposes a post-evaluation model based on game theory to improve comprehensive weighting and fuzzy grey relational projection sorting,… More > Graphic Abstract

Haichen Li^1,2, Jianghai Li¹, Li Li^3,4,*, Zhandong Li^5,*

Energy Engineering, Vol.121, No.9, pp. 2435-2447, 2024, DOI:10.32604/ee.2024.050771 - 19 August 2024

Abstract The turbidite channel of South China Sea has been highly concerned. Influenced by the complex fault and the rapid phase change of lithofacies, predicting the channel through conventional seismic attributes is not accurate enough. In response to this disadvantage, this study used a method combining grey relational analysis (GRA) and support vector machine (SVM) and established a set of prediction technical procedures suitable for reservoirs with complex geological conditions. In the case study of the Huangliu Formation in Qiongdongnan Basin, South China Sea, this study first dimensionalized the conventional seismic attributes of Gas Layer Group… More >

Jianfeng Zhao^1,2, Yunliang Huo^1,2, Ji Xiong^1,*, Junbo Liu^1,2, Zhixing Guo¹, Qingxian Li³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1663-1678, 2024, DOI:10.32604/cmes.2023.030584 - 17 November 2023

Abstract To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform, a case-based reasoning framework is proposed. Specifically, a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties. In addition, AHP (Analytic Hierarchy Process) and entropy weight method are integrated to provide features weight, where both user preferences and comprehensive impact of the index have been concerned. Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.… More >

N. A. Maidin^1,2, S. M. Sapuan^1,*, M. T. Mastura², M. Y. M. Zuhri¹

Journal of Renewable Materials, Vol.11, No.5, pp. 2381-2397, 2023, DOI:10.32604/jrm.2023.026549 - 13 February 2023

Abstract Natural fibre reinforced polymer composite (NFRPC) materials are gaining popularity in the modern world due to their eco-friendliness, lightweight nature, life-cycle superiority, biodegradability, low cost, and noble mechanical properties. Due to the wide variety of materials available that have comparable attributes and satisfy the requirements of the product design specification, material selection has become a crucial component of design for engineers. This paper discusses the study’s findings in choosing the suitable thermoplastic matrices of Natural Fibre Composites for Cyclist Helmet utilising the DMAIC, and GRA approaches. The results are based on integrating two decision methods More >

Jiahao Wen, Zhijian Wang^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 749-765, 2023, DOI:10.32604/cmes.2023.023865 - 05 January 2023

Abstract Since the existing prediction methods have encountered difficulties in processing the multiple influencing factors in short-term power load forecasting, we propose a bidirectional long short-term memory (BiLSTM) neural network model based on the temporal pattern attention (TPA) mechanism. Firstly, based on the grey relational analysis, datasets similar to forecast day are obtained. Secondly, the bidirectional LSTM layer models the data of the historical load, temperature, humidity, and date-type and extracts complex relationships between data from the hidden row vectors obtained by the BiLSTM network, so that the influencing factors (with different characteristics) can select relevant… More >

Qi Zhuang^a,* , Zhuo Chen^b, Dong Liu^c, Yangyang Tian^d

Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-8, 2022, DOI:10.5098/hmt.19.19

Abstract In order to improve the accuracy and efficiency of wax deposition rate prediction of waxy crude oil in pipeline transportation, A GRA-IPSO-ELM model was established to predict wax deposition rate. Using Grey Relational Analysis (GRA) to calculate the correlation degree between various factors and wax deposition rate, determine the input variables of the prediction model, and establish the Extreme Learning Machine (ELM) prediction model, improved particle swarm optimization (IPSO) is used to optimize the parameters of ELM model. Taking the experimental data of wax deposition in Huachi operation area as an example, the prediction performance More >

Ngoc Thai Huynh¹, Tien V. T. Nguyen², Quoc Manh Nguyen^3,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5961-5983, 2022, DOI:10.32604/cmc.2022.029484 - 28 July 2022

Abstract To achieve high work performance for compliant mechanisms of motion scope, continuous work condition, and high frequency, we propose a new hybrid algorithm that could be applied to multi-objective optimum design. In this investigation, we use the tools of finite element analysis (FEA) for a magnification mechanism to find out the effects of design variables on the magnification ratio of the mechanism and then select an optimal mechanism that could meet design requirements. A poly-algorithm including the Grey-Taguchi method, fuzzy logic system, and adaptive neuro-fuzzy inference system (ANFIS) algorithm, was utilized mainly in this study.… More >

Manar B. AL-Hajji^1,*, Nabeel Abu Shaban², Shahnaz Al Khalil², Ayat Al-Jarrah³

Energy Engineering, Vol.118, No.5, pp. 1425-1438, 2021, DOI:10.32604/EE.2021.016413 - 16 July 2021

Abstract Solar energy is regarded as one of the promising renewable energy sources in the world.The main aim of this study is to use the Taguchi-Grey relational grade analysis to optimize the performance of two Solar Air Heaters (SAHs). A typical Grey–Taguchi method was applied. The Orthogonal Array, Signal-to-Noise ratio, Grey Relational Grade, and Analysis of Variance were employed to investigate the performance characteristics of SAH. Experimental observations were made in agreement with Jordanian climate 32°00′ N latitude and 36°00′ E longitude with a solar intensity of 500 W\m². The operating factors selected for optimization are the… More >

Diantao Hu, Cong Zhang^*, Wenqi Cao, Xintao Lv, Songwu Xie

Journal on Big Data, Vol.3, No.2, pp. 65-76, 2021, DOI:10.32604/jbd.2021.016317 - 13 April 2021

Abstract Grain yield security is a basic national policy of China, and changes in grain yield are influenced by a variety of factors, which often have a complex, non-linear relationship with each other. Therefore, this paper proposes a Grey Relational Analysis–Adaptive Boosting–Support Vector Regression (GRAAdaBoost-SVR) model, which can ensure the prediction accuracy of the model under small sample, improve the generalization ability, and enhance the prediction accuracy. SVR allows mapping to high-dimensional spaces using kernel functions, good for solving nonlinear problems. Grain yield datasets generally have small sample sizes and many features, making SVR a promising… More >