Titlebook: Intelligent Data Engineering and Automated Learning – IDEAL 2020; 21st International C Cesar Analide,Paulo Novais,Hujun Yin Conference proc

Corral

A Novel Metaheuristic Approach for Loss Reduction and Voltage Profile Improvement in Power Distribuion network to minimize active power loss and improve the voltage profile. The NNA is a novel developed optimizer based on the concept of artificial neural networks which benefits from its unique structure and search operators for solving complex optimization problems. The difficulty of tuning the i

弓箭

偏見(jiàn)

LSI Based Mechanism for Educational Videos Retrieval by Transcripts Processing,any systems. Since various indexing techniques are available, finding the suitable ingredients that build an efficient data analysis pipeline represents a critical task. The paper tackles the problem of retrieving top-N videos that are relevant for a query provided in the Spanish language at Univers

BINGE

袖章

Adaptation and Anxiety Assessment in Undergraduate Nursing Students,se or loneliness that are not easily overwhelmed, no doubt the educational character of each one comes into play, since the involvement of each student in academic practice depends on his/her openness to the world. In this study it will be analyzed and evaluated the relationships between academic ex

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引導(dǎo)

Using Kullback-Leibler Divergence to Identify Prominent Sensor Data for Fault Diagnosis, maintenance management, safer operation, and economic gains are three examples of benefits achieved by using this combination to monitor the equipment condition. In this context, the selection of meaningful information to train machine learning models arises as an important issue, since it influenc

evaculate

Condyle

Improving Adversarial Learning with Image Quality Measures for Image Deblurring,ovel component based on image quality measures in the objective function of GANs for solving image deblurring problems. Such additional constraints can regularise the training and improve the performance. Experimental results demonstrate marked improvements on generated or restored image quality bot

獨(dú)輪車

On Random-Forest-Based Prediction Intervals,ave inherent errors which should be quantified. Prediction intervals (PI) are a great alternative to point predictions, as they permit measuring the uncertainty of the prediction. In this paper, we review Quantile Regression Forests and propose five new alternatives based on them, as well as on . ra