Trend Analysis and Comprehensive Evaluation of Green Production Principal Component of Thermal Power Unit Based on ANP-MEEM Model by Zhongfu Tan, Qingkun Tan, Liwei Ju, Shenbo Yang, Huangfu Cheng, Jiale Ma

“…This paper takes the green development of electric power as the research direction, the thermal power unit is the green source control point of electricity, and the green production of the thermal power unit is the research target; based on the actual research data and the actual data, the comprehensive evaluation of the green production of a thermal power generating unit in a city is carried out by means of ANP, matter-element extension model, and principal component analysis. This paper not only reflects the quantification of green benefits in each year, but also achieves the comparison of green achievements and the analysis of increasing losses in the data years. …”
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Integrating principal component analysis, fuzzy inference systems, and advanced neural networks for enhanced estuarine water quality assessment by Richard O. Usang, Bamidele I. Olu-Owolabi, Kayode O. Adebowale

“…New hydrological insights for the region: The hybrid LSTM-CNN model demonstrated superior predictive performance, achieving RMSE values lower than 10 % and R² values exceeding 0.90 across various predictive tasks, indicating high accuracy in forecasting water quality parameters. …”
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Unsupervised Identification for 2-Additive Capacity by Principal Component Analysis and Kendall’s Correlation Coefficient in Multi-Criteria Decision-Making by Xueting Guan, Kaihong Guo, Ran Zhang, Xiao Han

“…During the process, some significant results are achieved. Firstly, the Shapley values of decision criteria are derived by using the PCA, through a combination of the variance contribution rate of each Principal Component (PC) and its corresponding eigenvector. …”
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Nuclear Magnetic Resonance Fingerprinting and Principal Component Analysis Strategies Lead to Anti-Tuberculosis Natural Product Discovery from Actinomycetes by Jianying Han, Xueting Liu, Lixin Zhang, Ronald J. Quinn, Miaomiao Liu

“…Additionally, elaiophylin and polycyclic tetramate macrolactams (PTMs) displayed significant bactericidal effects, with elaiophylin achieving complete BCG inhibition at 72 h and PTMs marking their first reported anti-TB activity. …”
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Identifying Significant Macroeconomic Indicators for Indian Stock Markets by Prakash K. Aithal, Acharya U. Dinesh, M. Geetha

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PW-FBPNN: A Hybrid Fault Diagnosis Method for Power Circuit Systems Combining Principal Component Analysis, Wavelet Packet Transform, and Fuzzy Neural Networks by Xu Chen, Chao Zhang, Haomiao Zhang, Zhiqiang Cheng, Yu Yan

“…This study proposes a novel hybrid method, PW-FBPNN, which integrates principal component analysis (PCA), wavelet packet transform (WPT), and fuzzy back propagation neural network (FBPNN) to enhance fault diagnosis. …”
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Research on FTTR WLAN indoor wireless location algorithm based on frequency response by Zhifeng LONG, Jing ZHANG

“…Highly accurate and reliable indoor wireless positioning services have been widely used.In order to obtain good positioning accuracy, the design of positioning algorithms needs to be matched with wireless positioning facilities.fiber to the room (FTTR) is an indoor access network solution based on IEEE 802.11 ax, a new generation of wireless local area network (WLAN) standard.Compared with the existing Wi-Fi networks, FTTR has a much larger available band width.However, FTTR WLAN also lacks of a public valid data set to support localization functions, which makes the localization research based on FTTR scenarios face huge obstacles.In order to solve the above problems, firstly, a frequency response-based FTTR scene dataset generation method was proposed, which uses the existing Wi-Fi localization dataset to generate the frequency response matrix within the available band width of FTTR.Then, the parallel path principal component analysis (PCA) method was used to generate the classification matrix.And the generated dataset was trained using a fully connected neural network to improve the accuracy.The experimental results on the real measurement dataset show that the proposed localization algorithm can achieve a localization accuracy of less than 1 m, which is not only more accurate than the traditional location estimation algorithm, but also basically meets the fine-grained localization requirements for practical applications.…”
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The current framework of Development Education in Spain: achievements and challenges by Sarah CARRICA-OCHOA, Aurora BERNAL-MARTÍNEZ-DE-SORIA

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Multi-Component Temporal-Correlation Seismic Data Compression Algorithm Based on the PCA and DWT by Mateus Martinez de Lucena, Josafat Leal Ribeiro, Matheus Wagner, Antônio Augusto Fröhlich

“…The proposed method can be tuned through threshold and quantization percentages and the number of principal components to achieve compression rates of up to 31:1 with reconstruction residues energy of less than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>%</mo></mrow></semantics></math></inline-formula> in the frequency ranges of 0–20 Hz, 15–65 Hz, and 60–105 Hz.…”
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Antecedents and consequences of professional competence of school administrators with emphasis on environmental sustainability and sustainable development by mohamadreza rasouli, ghafar tari, hossein Baghaei

“…In order to validate the professional competence of school principals as an effective and key driver of sustainable development, the proposed conceptual model was investigated through structural equation modelling, and the partial least squares method was used to estimate the model. …”
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Quelles frontières pour les populations cholanes ? by Cédric Becquey

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Comparison of Feature Selection and Feature Extraction Role in Dimensionality Reduction of Big Data by Haidar Khalid Malik, Nashaat Jasim Al-Anber, Fuad AbdoEsmail Al- Mekhlafi

“…We applied many classifiers like (Support vector machines, k-nearest neighbors, Decision tree, and Naive Bayes ) to the data of the anthropometric survey of US Army personnel (ANSUR 2) to classify the data and test the relevance of features by predicting a specific feature in USA Army personnel results showing that (k-nearest neighbors) achieved high accuracy (83%) in prediction, then reducing the dimensions by several techniques like (Highly Correlated Filter, Recursive  Feature Elimination, and principal components Analysis) results showing that (Recursive  Feature Elimination) have the best accuracy by (66%), From these results, it is clear that the efficiency of dimension reduction techniques varies according to the nature of the data. …”
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Public Administration Digitalization and Government Effectiveness in EU Countries by Armenia Androniceanu, Irina Georgescu

“…A K-means clustering with four clusters reveals that the most significant and noteworthy increase in digitalization and government effectiveness in the EU is achieved by the Nordic countries, which exhibit high levels of digitalization and government efficiency. …”
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BASELINE PLASMA CHOLINESTERASE ACTIVITIES IN ARGENTINE SADDLE HORSES FROM SABANA DE BOGOTÁ by C. Ariza, M. E. Forero, M. Pedraza, J. F. González

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Spatiotemporal heterogeneity management: Optimizing the critical role of ecosystem services in achieving Sustainable Development Goals by Lingli Zuo, Guohua Liu, Junyan Zhao, Jiajia Li, Shuyuan Zheng, Xukun Su

“…These findings substantiate the need for integrated management of multiple ESs and facilitate the regional achievement of SDGs in geographically intricate areas.…”
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The Concept of Freedom and Its Boundaries: A Critical Look at Content, Methodology, Claims of Nigel Warburton’s Book by Ghadir Nasri

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The determinants of severe food insecurity in Africa using the longitudinal generalized Poisson mixed model by Adusei Bofa, Temesgen Zewotir

“…Our findings provide insight concerning Africa which will help policymakers create targeted plans for Africa that will address issues with food security and nutrition, and this will fuel the achievement of Sustainable Development Goal 2. …”
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Well-Production Forecasting Using Machine Learning with Feature Selection and Automatic Hyperparameter Optimization by Ruibin Zhu, Ning Li, Yongqiang Duan, Gaofeng Li, Guohua Liu, Fengjiao Qu, Changjun Long, Xin Wang, Qinzhuo Liao, Gensheng Li

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Optimizing boron application methods and dosages to enhance jute (Corchorus olitorius) seed yield and quality under sub-tropical climate by Tapan Kumar, Pritthee Mallick Tama, Syed Aflatun Kabir Hemel, Ranjit Kumar Ghosh, Md Imran Ali, Abdullah Al-Bakky, Abdul Alim

“…So, 3.0 kg/ha foliar boron treatment, applied half at 20–25 days after sowing and the remainder at the first flowering stage is recommended for late jute seed production to achieve optimum seed yield and net profit.…”
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Detecting Anomaly Classification Using PCA-Kmeans and Ensembled Classifier for Wind Turbines by Prince Waqas Khan, Yung-Cheol Byun

“…This can ultimately contribute to achieving a sustainable and renewable energy future.…”
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