Learning model combined with data clustering and dimensionality reduction for short-term electricity load forecasting by Hyun-Jung Bae, Jong-Seong Park, Ji-hyeok Choi, Hyuk-Yoon Kwon

“…Abstract Electric load forecasting is crucial in the planning and operating electric power companies. It has evolved from statistical methods to artificial intelligence-based techniques that use machine learning models. …”
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Probabilistic forecasting of renewable energy and electricity demand using Graph-based Denoising Diffusion Probabilistic Model by Amir Miraki, Pekka Parviainen, Reza Arghandeh

“…Extensive experiments validate that our proposed method reduces the Continuous Ranked Probability Score (CRPS) by 2.1%–70.9%, Mean Absolute Error (MAE) by 4.4%–52.2%, and Root Mean Squared Error (RMSE) by 7.9%–53.4% over existing methods on two real-world datasets.…”
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An adaptive estimation method to predict thermal comfort indices man using car classification neural deep belief by Alireza Entezari, Fatemeh Mayvaneh, Khosro Rezaie, Fatemeh Rahimi

“…The results showed that the most severe cold temperature stress on PMV index is in the winter and late autumn and UTCI index in January and February are the coldest stress. The power of neural networks, prediction of future performance network (generalized orientation) it simply is not possible and the new model presented in this paper have been restricted Boltzmann machine-based neural networks or neural networks is used deep belief. …”
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ON THE THIN PRACTICAL RATIONALITY AND ITS THICKENINGS by Zenonas Norkus

“…Frankfurt gives handy means to demarcate the bounds of practical rationality too: human agents cannot pretend to achieve the absolute practical rationality in their choices because they in their choices of the preferences (or ethical preferences) cannot rely on arguments having the validating power not coming up to that possessed by the arguments substantiating the choices between the empirical hypotheses. …”
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Estimation of Total Suspended Solids Concentration in Streams Using Regression and Artificial Neural Networks Methods by Betül Mete, Sinan Nacar, Adem Bayram, Osman Tuğrul Bak

“…Compared to other functions, the power one had the best estimation results in the regression analysis. …”
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Experimental Validation of Virtual Torque Sensing for Wind Turbine Gearboxes Based on Strain Measurements by Jelle Bosmans, Simone Gallas, Victor Smeets, Matteo Kirchner, Luk Geens, Jan Croes, Wim Desmet

“…ABSTRACT In efforts to reduce the operation and maintenance cost of wind turbines, there is an increasing interest to monitor key turbine quantities such as the torque load on the gearbox. …”
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The Algorithm for Predicting the Numerical Value of Salivary Cortisol Based on Heart Rate Variations in the Healthy Men by Mohammad Reza Noruzi, Marzieh Barzegar, Mahdi Alizadeh, Boshra Hatef

“…Conclusion: In this study, it was found that a set of linear and non-linear indicators of HRV with high power can predict the amount of salivary cortisol in the best case with a low error percentage of 7.43 by the RBF algorithm, and instead of stress self-report that does not cover the physiological part. …”
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Evaluation of an Information Flow Gain Algorithm for Microsensor Information Flow in Limber Motor Rehabilitation by Naiqiao Ning, Yong Tang

“…After the noise is removed, the signal is extracted in the time domain and frequency domain, and the root mean square (RMS), absolute mean, median frequency in the time domain, and average power frequency in the frequency domain are selected and input to the classifier for pattern recognition. …”
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Environmental Characteristics of Modern Systems of Domestic Use of Fuel. Part 2. Pollutants Formation by Natural Gas Combustion in Atmospheric Burners: Experimental Studies by B. S. Soroka, V. V. Horupa

“…Carbon oxides CO and nitrogen oxides NO and NO2 are considered as toxic emissions, while the primary air excess coefficient and the heat load of the burner are considered as variable parameters. Under operating conditions of a gas stove, its variable characteristics are the gas pressure in front of the nozzle of the atmospheric burner and its thermal power. …”
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Scientific and Methodological Bases of Exergetic Analysis of the Processes of Heat Treatment of Concrete Products in Heat Technology Installations. Part 1 by V. N. Romaniuk, A. M. Niyakovskii

“…Having proven its effectiveness in finding the best options for energy supply and energy consumption the exergetic method of thermodynamic analysis of complex heat and power systems has been widely recognized in recent years. …”
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Predicting the risk of cardiovascular disease in adults exposed to heavy metals: Interpretable machine learning by Meiyue Shen, Yine Zhang, Runqing Zhan, Tingwei Du, Peixuan Shen, Xiaochuan Lu, Shengnan Liu, Rongrong Guo, Xiaoli Shen

“…A total of 4600 adults were included in the analysis. The Least Absolute Shrinkage and Selection Operator regression method was employed to select relevant feature variables. …”
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GENOME POLITICS: STRATEGY AND TACTICS by Jonas Rubikas

“…Human beings as all living Nature obey the bible trinity law: we are not only parents but also offsprins at the same time, we are joined to each other by the eternal renovation power - the GENOME. …”
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Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…The frequent bending of shearer cables during operation often leads to mechanical fatigue, posing risks to equipment safety. …”
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Prediction of the Bending Strength of Boltless Steel Connections in Storage Pallet Racks: An Integrated Experimental-FEM-SVM Methodology by Zhi-Jun Lyu, PeiCai Zhao, Qi Lu, Qian Xiang, HongLiang Li

“…Based on the M–θ curve of the FE simulation, support vector machines (SVMs) were trained to predict the flexural rigidity of beam-to-column joints. The predictive power of the SVM algorithms is estimated by comparison with traditional ANN models via the root mean square error (RMSE), the mean absolute percentage error (MAPE), and the correlation coefficient R. …”
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Effect of Ultrasonic Treatment on the in Vitro Digestibility Properties of Black Bean Protein by Rong'an CAO, Xuemin ZHANG, Jingjing DIAO, Yunhua CHEN, Meiqi LI, Jiamiao ZHANG, Changyuan WANG

“…For exploring the effect of ultrasonic treatment on the digestive characteristics, the black bean protein was treated by ultrasonication at different power (150, 200, 250, 300, 350 W) and duration (6, 12, 18, 24 min) in low frequency (20 kHz). …”
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Foucault in Sulawesi: Challenging the Roots of Ethnic Discourse in South Sulawesi by Muh Adnan Malewa

“…Additionally, the 1609-1669 conflict is addressed, using Michel Foucault’s theory of power relations and knowledge. This research discovered how ethnic polarization occurred and offers possible corrections and additions to previous historians’ historical interpretations based more on national interests than historic facts. …”
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Changes in Cardiac Tone Regulation with Fatigue after Supra-Maximal Running Exercise by Pierre-Marie Leprêtre, Philippe Lopes, Claire Thomas, Christine Hanon

“…HHR𝜏 measured after the 400 m running exercise was longer compared to 300 m running bouts (183.7±11.6 versus 132.1±9.8 s, 𝑃<0.01). Absolute power density in the LF and HF bands was also lower after 400 m compared to the 300 m trial (𝑃<0.05). …”
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“What is good for animals is good for men” : animalité et abject dans Found in the Ground de Howard Barker by Eléonore Obis

“…This article analyses the analogies between Howard Barker's theatre of Catastrophe and the abject as defined by Julia Kristeva in Powers of Horrors through the study of Found in the Ground, a play where there are many animals on the stage. …”
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Development and Validation of a Nosocomial Infection Nomogram Model in the NICU: A Novel and Nurse-Led Way to Prediction in Preterm Infants by Shang Y, Chen L, Hu X, Zhang K, Cheng Q, Shui X, Deng Z

“…Clinical data were collected and then analyzed by univariate analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate logistic regression analysis. …”
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Evaluating Normalization Methods for Robust Spectral Performance Assessments of Hyperspectral Imaging Cameras by Siavash Mazdeyasna, Mohammed Shahriar Arefin, Andrew Fales, Silas J. Leavesley, T. Joshua Pfefer, Quanzeng Wang

“…., area under the curve, standard normal variate, and centering power methods), followed by a uniform scaling step. …”
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