Comprehensive Benefit Evaluation for Prefabricated Buildings Based on NSGA-II and Simulated Annealing Optimization Projection Pursuit Method by Fang Wang, Binbin Dai, Shiyu Song

“…The results indicate that: (1) the optimal projection eigenvalue of the comprehensive benefit evaluation is 1.860, and applying this method to evaluate the comprehensive benefits of prefabricated buildings yields more comprehensive and objective results; (2) the best projection vector values are ENB<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {\ast }}$ </tex-math></inline-formula>(0.9944) &#x003E; SB<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {\ast }}$ </tex-math></inline-formula>(0.9422) &#x003E; EB<inline-formula> <tex-math notation="LaTeX">$^{\mathrm {\ast }}$ </tex-math></inline-formula>(0.0272), indicating that environmental benefits have the greatest impact on the projection eigenvalue of comprehensive benefits, while economic benefits have the least impact; (3) there is a certain positive correlation between economic benefits and social benefits, while there is a certain negative correlation with environmental benefits.…”
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Forecasting outbound student mobility: A machine learning approach. by Stephanie Yang, Hsueh-Chih Chen, Wen-Ching Chen, Cheng-Hong Yang

“…Without the requirements of any special conditions for the proprieties of the objective function and constraints, the FSDESVR model retained the advantage of FS, SVR, and DE. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Evaluated the performance of a system by using the following classifiers as Non-Linear Regression—NLR, Linear Regression—LR, Gaussian Mixture Model—GMM, Expectation Maximization—EM, Bayesian Linear Discriminant Analysis—BLDA, Softmax Discriminant Classifier—SDC, and Support Vector Machine with Radial Basis Function kernel—SVM-RBF classifier on two publicly available datasets namely the Nordic Islet Transplant Program (NITP) and the PIMA Indian Diabetes Dataset (PIDD). …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Calculation of hydrogen dispersion in cushion gases using machine learning by Ali Akbari, Mehdi Maleki, Yousef Kazemzadeh, Ali Ranjbar

“…Various ML models—including Random Forest (RF), Least Squares Boosting (LSBoost), Bayesian Regression, Linear Regression (LR), Artificial Neural Networks (ANNs), and Support Vector Machines (SVMs)—were employed to quantify KL as a function of pressure (P) and displacement velocity (Um). …”
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Research on Clothing Image Database Retrieval Algorithm Based on Wavelet Transform by Xiaoyue Cui

“…Firstly, it represents the color consistency vector of clothing image, reflects the composition and distribution of image color through color histogram, quantifies the visual features of clothing image, aggregates them into a fixed size representation vector, and uses the Fair Value (FV) model to complete the collection of clothing image data. …”
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The futures for regenerative agriculture: insights from the organic movement and the tussle with industrial agriculture by Tatenda Mambo, Guillaume Lhermie, Guillaume Lhermie

“…While the academic literature has cataloged various approaches to defining RA, each definitional approach carries with it a relative concern for its likelihood for co-optation and the potential transformative power it can have within the sector. As the industrial agrifoods sector is taking interest in the field, lessons from the organic movement are worth highlighting. …”
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Carbon Sequestration Potential of Paddy Soil in China under the Carbon Peaking and Carbon Neutrality Goals by Longlong Bai, Yaqi Sheng, Lili Xu, Xiang Gao, Yongxin Zhang, Jinsong Deng

“…These findings hold scientific significance and practical values in fully utilizing the carbon sink function of paddy soils, reducing greenhouse gas emissions, and advancing the "dual carbon" goals in the agricultural sector.…”
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Global projections of heat stress at high temporal resolution using machine learning by P. Georgiades, P. Georgiades, T. Economou, T. Economou, Y. Proestos, J. Araya, J. Lelieveld, J. Lelieveld, M. Neira

“…Dairy cattle, a crucial component of the livestock sector, are particularly vulnerable to heat stress, which can adversely affect milk production, immune function, and feed intake and, in extreme cases, lead to mortality. …”
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Novel Investigation of Multivariable Conformable Calculus for Modeling Scientific Phenomena by Mohammed K. A. Kaabar, Francisco Martínez, Inmaculada Martínez, Zailan Siri, Silvestre Paredes

“…An extension to vector-valued functions (VVFs) of several real variables (SRVs) is studied in this work. …”
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THE INFLUENCE OF ECONOMIC MENTALITY ON SOCIO-ECONOMIC DEVELOPMENT by Z. Halushka, V. Zapukhlyak, L. Klevchik, O. Luste, B. Storoshchuk

“…Authors underline inconsistenciesbetween the interaction of the formal and historically formed informal institutions actualizes the role of economic mentality, since it directly influences the general vector of socio-economic system development. The article draws attention to the informal component of the institutional environment — economic mentality, which haracterizes the historically formed values, motives and models of economic behavior of individual and collective actors that directly affect the overall vector of socio-economic system development and transformation.It is determined that economic mentality determines the dynamics of the institutional environment development of by influencing the effectiveness of formal and informal institutions interaction, ensuring the performance of complementary functions; mediates the process of institutionalization of historically determined values, stereotypes and models of economic behavior in the system of formal norms and rules; provides under the influence of other socio-economic factors adaptability and dynamism of nstitutional structure, promotes the formation and development of new institutions. …”
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Neural Network-Based Analysis of Forest Fire Aftermath in Class-Imbalanced Remote Sensing Earth Image Classification by V. Hnatushenko, V. Hnatushenko, V. Hnatushenko, D. Soldatenko

“…Today's agricultural sector is characterized by an important role of accurate mapping and monitoring of agriculture with the help of satellite imagery, which allows to optimize the use of resources, to plan crop areas and to forecast productivity. …”
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Self-Dual Effective Compact and True Compacton Configurations in Generalized Abelian Higgs Models by Rodolfo Casana, Guillermo Lazar, Lucas Sourrouille

“…The generalization of the kinetic terms is performed by means of dielectric functions in gauge and Higgs sectors. The implementation of the BPS formalism without the need to use a specific Ansatz has led us to the explicit determination for the dielectric function associated with the Higgs sector to be proportional to λϕ2λ-2, λ>1. …”
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Modified BFGS Update (H-Version) Based on the Determinant Property of Inverse of Hessian Matrix for Unconstrained Optimization by Saad Shakir Mahmood

“…The study presents the modification of the Broyden-Flecher-Goldfarb-Shanno (BFGS) update (H-Version) based on the determinant property of inverse of Hessian matrix (second derivative of the objective function), via updating of the vector s ( the difference between the next solution and the current solution), such that the determinant of the next inverse of Hessian matrix is equal to the determinant of the current inverse of Hessian matrix at every iteration. …”
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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…The model estimates eGFR using three established CKD Epidemiology Collaboration (CKD-EPI) equations incorporating SCr, SCysC, and their combined values. Regression models assess predictive performance, specifically Linear Regression (LR) and Support Vector Regression (SVR). …”
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EsoDetect: computational validation and algorithm development of a novel diagnostic and prognostic tool for dysplasia in Barrett’s esophagus by Migla Miskinyte, Benilde Pondeca, José B. Pereira-Leal, Joana Cardoso

“…Ultimately, a linear support vector machine algorithm incorporating ten genes was identified for diagnostic application, while a radial basis function support vector machine algorithm, also utilizing ten genes, was selected for prognostic prediction. …”
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Nitrogen Exchanges: Testing the Hypothesis of a Country without Agricultural Production by M.-F. Slak, L. Commagnac, P. Pointereau, S. Larbouret, C. Lucas, S. Muller

“…Calculations of such balances are carried out by most of the European countries as an indicator of environmental pollution attributable to the agricultural sector. In France, average values of agricultural nitrogen balances show an excess of 1.5 to 2 million tons of nitrogen. …”
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Gearbox Fault Diagnosis Using Complementary Ensemble Empirical Mode Decomposition and Permutation Entropy by Liye Zhao, Wei Yu, Ruqiang Yan

“…The presented approach identifies faults appearing in a gearbox system based on PE values calculated from selected intrinsic mode functions (IMFs) of vibration signals decomposed by CEEMD. …”
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GLOBALIZATION OF SOCIETY AS ONE OF THE MAIN FACTORS OF THE NEW BUSINESS COMMUNICATION DISCOURSE FORMATION by Olena M. Turchak

“…This problem is due to the functioning of the Ukrainian language in the context of bilingualism. …”
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Discrete traveling waves in a Toda’s relay chain by A.A. Kutuzova, M.M. Preobrazhenskaia, A.S. Tokmachev

“…The existence of the corresponding periodic solution of the system is ensured by the solvability of the period equation: the value (m+1)Δ must be a multiple of the period of the auxiliary function. …”
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