TÜRKİYE’DEKİ İLLERİN SOSYO-EKONOMİK GELİŞMİŞLİK DÜZEYLERİNİN BELİRLENMESİ by Hülya Şen, Fatih Çemrek, Özer Özaydın

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TÜRKİYE’DEKİ İLLERİN SOSYO-EKONOMİK GELİŞMİŞLİK DÜZEYLERİNİN BELİRLENMESİ by Hülya ŞEN, Fatih ÇEMREK, Özer ÖZAYDIN

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TÜRKİYE’DEKİ İLLERİN SOSYO-EKONOMİK GELİŞMİŞLİK DÜZEYLERİNİN BELİRLENMESİ by Hülya Şen, Fatih Çemrek, Özer Özaydın

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不同产地山桐子品质分析及综合评价 Quality analysis and comprehensive evaluation of Idesia polycarpa by 邹康，常云鹤，宋明发，刘晓燕，何劲，马立志 ZOU Kang, CHANG Yunhe, SONG Mingfa, LIU Xiaoyan, HE Jin, MA Lizhi

Subjects: “…山桐子；产地品质；脂肪酸组成；油脂伴随物；主成分分析 idesia polycarpa maxim; geographic region quality; fatty acid composition; lipid concomitant; principal component analysis…”
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Shedding light on biochemical changes in single neuron-like pheochromocytoma cells following exposure to synchrotron sourced terahertz radiation using synchrotron source Fourier tr... by Palalle G. Tharushi Perera, Jitraporn Vongsvivut, Denver Linklater, Zoltan Vilagosh, Dominique Appadoo, The Hong Phong Nguyen, Mark J. Tobin, Rodney Croft, Elena P. Ivanova

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Comparison of Extracellular Metabolites and Antioxidant Activity of Different Strains of Wolfiporia hoelen (Fr.) Y.C. Dai &V. Papp by TAN Yun, SHEN Airong, SHEN Baoming, YU Jinxiu, LIU Lina, LI Sainan, TAN Zhuming

Subjects: “…wolfiporia hoelen (fr.) y.c. dai &v. papp; extracellular metabolites; antioxidant activity; kaempferol-3-o-(6-galloyl)glucoside; α-cyano-4-hydroxycinnamic acid; principal component analysis; widely targeted metabolomics…”
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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

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FORMING AN ENVIRONMENTALLY SUSTAINABLE AGROPHYTOCENOSIS ON THE EXAMPLE OF MIXED CROPS OF GRASS PEA AND SUDAN GRASS IN THE NORTH-WEST OF THE RUSSIAN FEDERATION by M. O. Burlyaeva, A. E. Solovyeva

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Runoff Forecasting Research Coupling Quadratic Factor Screening and Deep Learning by CHENG Liwen, HUANG Shengzhi, LI Pei, LI Ziyan, JIA Songtao, HUANG Qiang

“…The effective screening of factors influencing runoff is a key aspect of runoff forecasting research.However,there are many factors affecting runoff,and these factors have complex interactions.Most of the existing studies use numerically driven models with primary factor screening,and the results show that the input factors are spatially redundant,leading to poor forecasting results.In view of this,the support vector regression (SVR) and the long-short memory network model (LSTM) are compared with Weihe River Basin as an example,and the LSTM model is selected as the optimal forecasting model.Principal component analysis and gray correlation analysis are used for secondary screening of the input terms to form a model coupling principal component analysis,gray correlation analysis,and LSTM.The results show that:①the fitting accuracy of LSTM is higher than that of SVR;②the secondary screening of the input terms improves the forecast accuracy,and the forecast accuracy of the coupled model is better than that of the single model,specifically,the model accuracy evaluation indexes of the coupled model are substantially improved compared with those of the single model;③the Nash efficiency coefficient and deterministic coefficient of the coupled model of gray system correlation analysis are improved by 0.13% and 0.03%,respectively,compared with those of the coupled model of principal component analysis,and the standard deviation ratio of observed values is improved by 42.9%.The study shows that the secondary factor screening by using gray correlation can effectively improve forecast accuracy.…”
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Feature Recognition of Crop Growth Information in Precision Farming by Hanqing Sun, Xiaohui Zhang, Zhou Yu, Gang Xi

“…Principal component analysis (PCA) is applied to treat the constructed features and eliminate redundant information among those features and extract features which can reflect signal type. …”
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Application of Optimized Support Vector Machine Model in Tax Forecasting System by Yu Xin

“…After grid search optimization, the introduction of principal component analysis reduces the redundancy and improves the prediction accuracy.…”
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Classification of reduction invariants with improved backpropagation by S. M. Shamsuddin, M. Darus, M. N. Sulaiman

“…This can be done by using a number of methods, such as principal component analysis (PCA), factor analysis, and feature clustering. …”
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Structural Damage Identification Based on the Transmissibility Function and Support Vector Machine by Yansong Diao, Xue Men, Zuofeng Sun, Kongzheng Guo, Yumei Wang

“…The detection accuracy of the proposed method with damage feature constructed by principal component analysis is superior to that constructed by wavelet packet decomposition.…”
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Monitoring the water quality of Belawan Sea for rearing asian seabass Lates calcarifer in a floating net cage system by Vina Iman Sari Lubis, Kukuh Nirmala, Eddy Supriyono, Yuni Puji Hastuti

“…Kata Kunci: indeks CCME WQI, indeks STORET, monitoring kualitas air, Perairan Belawan, principal component analysis (PCA) …”
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Comprehensive Monitoring of Complex Industrial Processes with Multiple Characteristics by Chenxing Xu, Jiarula Yasenjiang, Pengfei Cui, Shengpeng Zhang, Xin Zhang

“…To address this problem, a hybrid fault detection model based on PCA-KPCA-ICA-KICA-BI (Bayesian inference) is proposed, taking into account the advantages of principal component analysis (PCA), kernel principal component analysis (KPCA), independent component analysis (ICA), and kernel independent component analysis (KICA) in terms of dimensionality reduction and feature extraction. …”
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Factor structure of the Jefferson Scale for Empathy among medical undergraduates from South India by Samir Kumar Praharaj, Santosh Salagre, Podila Sathya Venkata Narasimha Sharma

“…Five factors were extracted using principal component analysis, which explained 60% of the variance. …”
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Quality Evaluation of Saposhnikovia divaricata (Turcz.) Schischk from Different Origins Based on HPLC Fingerprint and Chemometrics by Yuqiu Chen, Zhefeng Xu, Siying Gao, Tao Zhang, Changbao Chen

“…Cluster analysis divides the 33 batches of S. divaricata into 2 categories. Principal component analysis (PCA) roughly divides them into 4 categories. …”
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Study on Prediction of Coal-Gas Compound Dynamic Disaster Based on GRA-PCA-BP Model by Kai Wang, Kangnan Li, Feng Du

“…First, the weights of 13 influencing factors are sorted and screened by grey relational analysis. Next, principal component analysis is carried out on the influencing factors with high weight value to extract common factors. …”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…A publicly available raw osteosarcoma dataset was explored and then preprocessed using different combinations of data denoising techniques (including principal component analysis, mutual information gain, analysis of variance and Kendall’s rank correlation analysis) and data augmentation to derive seven different datasets. …”
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A Novel Two-Stage Spectrum-Based Approach for Dimensionality Reduction: A Case Study on the Recognition of Handwritten Numerals by Mohammad Amin Shayegan, Saeed Aghabozorgi, Ram Gopal Raj

“…Although there are different conventional approaches for feature selection, such as Principal Component Analysis, Random Projection, and Linear Discriminant Analysis, selecting optimal, effective, and robust features is usually a difficult task. …”
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