Relevant bibliographies by topics / GRA-PCA

Academic literature on the topic 'GRA-PCA'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "GRA-PCA"

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Hu, Guohua, Guoyan Meng, Qingshan Zhao, and Xiaoxia Zheng. "Emotion feature optimisation based on PCA-GRA analysis." International Journal of Computing Science and Mathematics 12, no. 4 (2020): 339. http://dx.doi.org/10.1504/ijcsm.2020.112673.

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Zheng, Xiaoxia, Guohua Hu, Qingshan Zhao, and Guoyan Meng. "Emotion feature optimisation based on PCA-GRA analysis." International Journal of Computing Science and Mathematics 12, no. 4 (2020): 339. http://dx.doi.org/10.1504/ijcsm.2020.10034918.

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Mishra, Yadvendra Kumar, Sanjay Mishra, and S. C. Jayswal. "Comparative Analysis of Grey Relational Analysis Integrated with the Principal Component Analysis and Analytic Hierarchy Process for Multiobjective Optimization of Inclined Laser Percussion Drilling in Carbon Fiber Reinforced Composites." Journal of Advanced Manufacturing Systems 21, no. 01 (February 11, 2022): 1–23. http://dx.doi.org/10.1142/s0219686721500475.

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Multiobjective optimization (MOO) helps to achieve simultaneous improvement of more than one output characteristic in machining processes where complex interaction between the input parameter exists. This study focuses on the comparative analysis of design of experiment (DoE)-based grey relational analysis (GRA) combined with principal component analysis (PCA) and analytic hierarchy process (AHP). Experiments were conducted with millisecond (ms) duration pulsed Nd: YAG laser using the Box–Behnken design (BBD) approach of the response surface methodology (RSM) at three different levels of input parameters. The output parameters, i.e., hole circularity at top (HCT), hole circularity at bottom (HCB), and hole taper (HT), were determined for various input parameters like pulse current (I), pulse width ([Formula: see text]), gas pressure ([Formula: see text]), workpiece thickness ([Formula: see text]), and incidence angle ([Formula: see text]) during laser percussion inclined hole drilling (LPIHD) in the carbon fiber reinforced polymer (CFRP) of three different thickness, i.e., 1[Formula: see text]mm, 3[Formula: see text]mm, and 5[Formula: see text]mm at incidence angles of 0, 10, and 20 degrees. Multiobjective function based on RSM has been developed for GRA-PCA and GRA-AHP and further optimizations were performed using the desirability approach of RSM. The analysis revealed that the angle of incidence is the most significant factor for controlling the output parameters. Interaction of pulse current and thickness ([Formula: see text]) has a major impact on output responses. The GRA-PCA approach gives the average improvement of 2%, 9%, and 37%, respectively, for HCT, HCB, and HT, whereas in the case of GRA-AHP, the corresponding improvements are only 1%, 6%, and 11%. Therefore, the GRA-PCA approach is a more effective tool for the MOO of LPIHD in CFRP.
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Jiang, Xuelian, Yueling Zhao, Ling Tong, Rui Wang, and Sheng Zhao. "Quantitative Analysis of Tomato Yield and Comprehensive Fruit Quality in Response to Deficit Irrigation at Different Growth Stages." HortScience 54, no. 8 (August 2019): 1409–17. http://dx.doi.org/10.21273/hortsci14180-19.

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To investigate the quantitative response of tomato yield and fruit quality to deficit irrigation applied at different growth stages, greenhouse experiments were conducted in 2017 and 2018. Three irrigation treatments (full irrigation and two-thirds or one-third of full irrigation) were applied to greenhouse-grown tomato plants at flowering and fruit development (stage 2) and at fruit maturation stage (stage 3). Grey relational analysis (GRA), the technique for order preference by similarity to an ideal solution (TOPSIS), and principal components analysis (PCA) were used to calculate the comprehensive fruit quality indexes, and combinatorial evaluation method was determined. The results showed that deficit irrigation significantly reduced evapotranspiration (ET) and tomato yield and that relative yield had a negative linear correlation with relative seasonal water deficit (1−ETi/ETc). However, deficit irrigation improved fruit quality, especially at stage 2. Total soluble solids, the total soluble sugar concentration, the sugar-to-acid ratio, and vitamin C in the tomatoes all increased significantly in plants that were deficit irrigated compared with fully irrigated plants, while organic acids and lycopene decreased in both years. There were linear correlations between fruit quality parameters and 1−ETi/ETc. The comprehensive quality index derived from GRA and PCA is reliable, and the comprehensive quality indexes given by GRA, PCA, and a combination of GRA and PCA showed positive linear correlation with 1−ETi/ETc. The comprehensive quality ranking showed that in both years, F2/3M1 (two-thirds full irrigation at stage 2) gave a better result and CK (full irrigation) the worst. An appropriate water deficit at the flowering and fruit development stage, which results in a trade-off between acceptable yield and improved fruit quality, is recommended. Our results provide a sound basis for tomato production that has a desirable balance between high yield and high fruit quality.
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Zhou, Yongqin, Yujia Chang, Yongchao Wang, and Ran Li. "Research on methods for extracting aging characteristics and health status of lithium-ion batteries based on small samples." Journal of Renewable and Sustainable Energy 14, no. 2 (March 2022): 024101. http://dx.doi.org/10.1063/5.0071686.

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The number of aging samples is small with regard to the small sample characteristics of lithium-ion battery aging data, and the extraction of effective aging features is difficult to perform, which reduces the generalization of the battery aging behavior model as well as the accuracy of battery state of health (SOH) estimation. According to the incremental capacity analysis, a gray relational analysis (GRA) method based on PCA (principal component analysis) was proposed in this study, which was combined with AdaBoost-SVR (support vector regression) to achieve accurate SOH measurement under small sample conditions. Accordingly, the combination of GRA and PCA was able to fully mine the aging characteristic information from limited battery aging samples while improving the generalization ability of the battery aging behavior model. Moreover, based on AdaBoost-SVR, it was able to perform adaptive weighted sampling on small data samples, and through multiple iterations of the SVR training model, the full use of small sample information was realized, ensuring the accuracy of SOH estimation. Finally, by employing multiple sets of battery aging training sets and test sets for experimental verification, the joint algorithm based on GRA-PCA and AdaBoost-SVR was proven to achieve the accurate extraction of battery aging characteristics and precise tracking of capacity decline.
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Ekici, Ergün, Ali Motorcu, and Gültekin Uzun. "Multi-objective optimization of process parameters for drilling fibermetal laminate using a hybrid GRA-PCA approach." FME Transactions 49, no. 2 (2021): 356–66. http://dx.doi.org/10.5937/fme2102356e.

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This study investigated the effects of drilling parameters and cutting tool coating conditions on the thrust force, surface roughness, and delamination factor in the drilling of fiber-reinforced carbon reinforced aluminum laminate (CARALL) composite, a commercial type of fibermetal laminate. Gray relational analysis (GRA) was used as a multi-objective optimization method to determine optimum processing parameters and principal component analysis (PCA) was used to determine the weights. According to the findings of this experimental study, the most effective control factors for the thrust force, surface roughnes, and delamination factor were the feed rate, tool coating condition-cutting speed interaction, and tool coating condition, with 93.87%, 66.504%, and 29.137% contribution rates, respectively. From the results of the GRA-PCA analysis, the optimum levels of the control factors were determined as 110 m/min cutting speed, 0.1 mm/rev feed rate, and the uncoated tool.
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LAKSHMI SRINIVAS, CH, P. UMAMAHESWAR RAO, T. SRINAG, and M. C. SEKHAR. "Grey Relational Analysis and Principal Component Analysis based optimization of process parameters in turning of EN-8 Steel." INCAS BULLETIN 14, no. 2 (June 10, 2022): 43–51. http://dx.doi.org/10.13111/2066-8201.2022.14.2.4.

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The present work investigates the optimum machining parameters while turning EN 8 steel by employing hybrid Grey relational analysis (GRA) and principal component analysis (PCA) techniques. Experiments were designed based on the central composite design (CCD) of the Response surface method (RSM). Experiments were conducted by varying machining parameters such as cutting speed, feed, and depth of cut. In this study, the surface roughness and the material removal rate (MRR) are measured during the experimentation. To determine the influence of cutting parameters, an Analysis of variance (ANOVA) was deployed. The optimal turning parameters are found to be speed 1170 rpm, feed 0.225 mm/rev, and depth of cut 1.238 mm. The results revealed that the optimization through hybrid GRA-PCA enhanced the output quality characteristics.
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Li, Zhiyong, Wanting Xi, Yuan Cao, and Shiping Pu. "A Dimensional Reduction Optimization Strategy for Line Voltage cascade Quasi-Z-Source Inverter Based on GRA-PCA-PSO." Journal of Physics: Conference Series 2488, no. 1 (May 1, 2023): 012053. http://dx.doi.org/10.1088/1742-6596/2488/1/012053.

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Abstract Compared with traditional inverters, line voltage cascade quasi-Z source inverter (LVC-QZSI) has many advantages, but its power quality problems limit its wide application to some extent. In this paper, voltage ripple and power loss of LVC-QZSI are selected as the optimization objectives to build a multi-objective optimization model of LVC-QZSI. In the optimization process, it is found that the dimension of decision variables is too high, which belongs to a kind of large-scale multi-objective optimization problem. To solve this problem, this paper proposes the dimension reduction and optimization strategy of particle swarm optimization based on gray relation analysis and principal component analysis (GRA-PCA-PSO). GRA-PCA is used to realize the dimension reduction of decision variables, and then PSO based on information entropy is used to optimize the multi-objective optimization model after dimension reduction. Finally, the original optimization parameter values are derived from the eigenvalue matrix obtained from PCA. Compared with the traditional method of decision variable grouping and co-evolution, it reduces the calculation cost and improves the optimization accuracy. Finally, we verify the reliability of the algorithm.
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Kumar, Anil, Arindam Kumar Chanda, and Surjit Angra. "Optimization of Stiffness Properties of Composite Sandwich using Hybrid Taguchi-GRA-PCA." Evergreen 8, no. 2 (June 2021): 310–17. http://dx.doi.org/10.5109/4480708.

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Xue, Feng, Qian Huang, Chuanlei He, and Bharat Pathak. "Using an Entropy-GRA, TOPSIS, and PCA Method to Evaluate the Competitiveness of AFVs – The China Case." Promet - Traffic&Transportation 32, no. 5 (October 5, 2020): 655–66. http://dx.doi.org/10.7307/ptt.v32i5.3417.

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With the increase in severe environmental problems associated with fossil fuel vehicles, the development of Alternative Fuel Vehicles (AFVs) has led to their promotion and use in Chinese provinces and cities. The comprehensive evaluation of competitiveness of the AFV industry in Chinese cities is beneficial to analyse the effects and relationships of different factors to promote the sustainable development of the AFV industry and guide the growth paths of the cities. An industrial competitiveness evaluation index system is established based on the characteristics of AFVs, and the development of the AFV industry in ten typical cities in China is comprehensively evaluated based on the Grey Relative Analysis (GRA) Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Principal Component Analysis (PCA) methods. To evaluate the results, the entropy weighting method is used for the weight distribution, and the industrial competitiveness rankings of ten cities are obtained by the entropy-GRA, TOPSIS, PCA (EGTP) method. The results show that Beijing is ranked first, followed by Shanghai, and Qingdao is ranked last. By analysing the correlation between the evaluation methods and indicators, it is found that EGTP has a high correlation with the other three evaluation methods, which proves the rationality of the weighted linear combination of GRA and the other three methods. Indices C5 (pure electric car proportion) and C13 (average concentration of PM2.5) were outliers due to the small number of samples.
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Dissertations / Theses on the topic "GRA-PCA"

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DHULL, SACHIN. "INVESTIGATION OF HYBRID ELECTROCHEMICAL AND MAGNETIC FIELD ASSISTED ABRASIVE FLOW FINISHING PROCESS." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18780.

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The current scenario of industrialization requires need for higher productivity which is met by advanced material removal process, i.e., abrasive flow machining (AFM) in which the internal surfaces of the workpiece is machined to higher accuracy level with the help of abrasive laden media. In this paper, the conventional AFM setup has been made hybrid using electrolytic and magnetic force arrangement alongwith rotational effect in order to achieve better results in terms of material removal and surface roughness. The newly developed in-house polymer media were utilized in the process and the input parameters taken during experimentation were magnetic flux, electrolytic rod size and shape, rotational speed, polymer media, abrasive particles and extrusion pressure. It was found that the material removal and surface roughness improvement were more in electrochemo magneto rotational AFM process compared to conventional AFM process. The experimental values were in confirmation with those obtained in the optimization techniques applied, i.e., Taguchi L9 OA, Matlab fuzzy logic and GRA-PCA. In addition, the hybrid mathematical model was developed and effect of different forces occurring in the process and computational flow analysis of media have been explained. With advent of need for fast productivity in terms of material removal and surface roughness of the workpiece, abrasive flow machining (AFM) process is gaining rapid importance in the industries. In this process, the fine finishing of the internal surfaces is done that are difficult to reach spaces using abrasive laden polymer media. The media is extruded past the surface under high pressure with the help of two sets of extrusion piston cylinder arrangements. Further various innovations done in the field of abrasive flow machining have been studied in detail in a tabulated form. It included the applications of the process and the different variant forms of AFM process. Hence it can be concluded that this form of non conventional machining process is efficient both in terms of surface roughness and material removal. The SBR media resulted in maximum material removal during experimentation, i.e., 3.88 mg when input parameters, i.e., electrolytic voltage, number of extrusion cycles and pressure were taken as 18 V, 4 and 10 bar respectively. The NR, NTR and SR media had intermediate effect of material removal but minimum removal of material was achieved in case of PBS media, i.e., 2.39 mg at 6 V voltage, 6 number of cycles and 30 bar pressure. The material removal was first increased with higher rod size but afterwards its increase was lesser. The surface plots obtained from RSM technique showed that MR obtained was 2.25 mg at 21 bar pressure and 7 number of cycles. As compared to conventional AFM setup, it was found that in EMR-AFM setup, 34.5 % and 17.8 % improvement in % Ra and material removal, respectively, was obtained. It was found that MR was approximately 2.9 mg on an average when machining was done on traditional AFM process, while it increased upto 4.5 mg in prepared hybrid machine setup.
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Chiou, BO-JR, and 邱柏智. "Dynamic Face Recognition based on PCA and GRA." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/68075835932791870681.

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碩士
國立臺灣師範大學
機電科技研究所
95
Face recognition systems have been utilized in areas such as biometric identity authentification, acess surveillance, and human-computer interface. More recently, because of the promotion of “intelligent life”, the use of face recognition techniques has been extended to optimizing the human-computer interface. In addition, video conferencing, image content indexing and medical diagnostics are other applications for face recognition. This paper first discusses the face detection part, and then discusses the face recognition part. For the face detection part, we used skin color segmentation and connected component method to extract a face candidate. Then color analysis was used to identify the features (lips, eyes) of the face candidate. Finally, measurements related to the eyes and mouth were used to locate the position of the face. For the face recognition part, we present a hybrid face recognition method, which combines Principal Component Analysis and Grey Relational Analysis. The proposed method consists of three stages. First, during preprocessing, we performed a Discrete Wavelet Transformation for data compression. Second, using Principal Component Analysis to project the input images into a low dimension subspace, we calculated the representative eigenface. Finally, we used Grey Relational Analysis to recognize the face images. To confirm our proposed method, we performed static and dynamic recognition experiments for analysis and comparison. ORL face databases were used in the static recognition experiments. Our database contained 40 people, and for each person, we selected 5 training samples. Using these training samples, we obtained an accuracy rate of 91.6 percent. In dynamic recognition experiments, we were able to obtain greater than 80 percent accuracy for 30 people under different distances.
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Khandey, Umesh. "Imrovement in turning of Al-SiC(25%Vol.)MMC and optimization of the important process parameters." Thesis, 2018. http://localhost:8080/iit/handle/2074/7643.

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Book chapters on the topic "GRA-PCA"

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Kumar, Vikas, and Rajesh Kumar Verma. "PCA-GRA Coupled Multi-criteria Optimisation Approach in Machining of Polymer Composites." In Numerical Optimization in Engineering and Sciences, 477–87. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3215-3_47.

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Ravi Sankar, B., and P. Umamaheswarrao. "Multi-response Optimization of End Milling on Al6061–Sicp Metal Matrix Composite–Hybrid GRA-PCA Approach." In Advances in Forming, Machining and Automation, 451–59. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9417-2_37.

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Kumar, Sandeep, and Abhishek Singh. "Multi-objective Optimization of Green Drilling Parameters on HcHcr Steel Using GRA-TOPSIS with PCA Method." In Lecture Notes in Mechanical Engineering, 13–23. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7709-1_2.

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Devarasiddappa, D., and M. Chandrasekaran. "PCA-GRA Integrated Multi Response Optimization of Wire-Cut EDM of Ti–6Al–4V Alloy for Sustainable Production." In Advances in Mechanical Engineering, 257–69. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0124-1_24.

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Umamaheswarrao, P., D. Ranga Raju, K. N. S. Suman, and B. Ravi Sankar. "Determination of Optimal Cutting and Tool Geometry Parameters for Better Surface Integrity of Hard Turned AISI 52100 Steel-Hybrid GRA-PCA." In Lecture Notes on Multidisciplinary Industrial Engineering, 297–308. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9072-3_25.

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Arif, Md Tasnim, and Amit Sharma. "Optimization of MRR and TWR in Electric Discharge Drilling of Ti-Alloy Using Hybrid Approach of Taguchi-Based GRA and PCA." In Lecture Notes in Mechanical Engineering, 339–49. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1328-2_31.

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James D, Jafrey Daniel, N. Ganesh, and Pandian G. Karthik. "Machinability Analysis and Optimization by the Taguchi-gra-pca Approach of PMEDM Process Parameters of Monel K 500." In Functional Composite Materials: Manufacturing Technology and Experimental Application, 19–34. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/9789815039894122010005.

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Conference papers on the topic "GRA-PCA"

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Li, Shengnan, Huaixiu Wang, and Yahui Wang. "The Gas Regulator Fault Diagnosis Based on PCA-GRA Combined Algorithm." In 2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020. http://dx.doi.org/10.1109/ccdc49329.2020.9163913.

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Pagar, Nitin D., and Amit R. Patil. "Life Augmentation of Turbine Exhaust System Compensators Through Integrated MADM Optimization Approach of Stress Based Fatigue Cycles." In ASME 2021 Gas Turbine India Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/gtindia2021-76690.

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Abstract Exhaust expansion joints, also known as compensators, are found in a variety of applications such as gas turbine exhaust pipes, generators, marine propulsion systems, OEM engines, power units, and auxiliary equipment. The motion compensators employed must have accomplished the maximum expansion-contraction cycle life while imposing the least amount of stress. Discrepancies in the selecting of bellows expansion joint design parameters are corrected by evaluating stress-based fatigue life, which is challenging owing to the complicated form of convolutions. Meridional and circumferential convolution stress equations that influencing fatigue cycles are evaluated and verified with FEA. Fractional factorial Taguchi L25 matrix is used for finding the optimal configurations. The discrete design parameters for the selection of the suitable configuration of the compensators are analysed with the help of the MADM decision making techniques. The multi-response optimization methods GRA, AHP, and TOPSIS are used to determine the parametric selection on a priority basis. It is seen that weighing distribution among the responses plays an important role in these methods and GRA method integrated with principal components shows best optimal configurations. Multiple regression technique applied to these methods also shows that PCA-GRA gives better alternate solutions for the designer unlike the AHP and TOPSIS method. However, higher ranked Taguchi run obtained in these methods may enhance the suitable selection of different design configurations. Obtained PCA-GRG values by Taguchi, Regression and DOE are well matched and verified for the all alternate solutions. Further, it also shows that stress based fatigue cycles obtained in this analysis for the L25 run indicates the range varying from 1.13 × 104 cycles to 9.08 × 105 cycles, which is within 106 cycles. This work will assist the design engineer for selecting the discrete parameters of stiff compensators utilized in power plant thermal appliances.
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