The gathered results from the application of three cases indicate that Multinomial Nave Bayes and Extra Trees machine learning algorithms give the best results with an F-measure value over 80%. The study aims to provide a quick response to earthquakes by applying the aforementioned techniques....
This has triggered the rapid development of machine learning (ML) models that can provide predictions through a self-learning process based on existing collected data. The bigger the data, the more reliable and accurate the predictions. Among these trends, ML techniques have been applied to ...
Classifying Gait Data Using Different Machine Learning Techniques and Finding the Optimum Technique of ClassificationThe Classification of Humanoid locomotion is a troublesome exercise because of nonlinearity associate with gait. The high dimension feature vector requires a high computational cost. The......
In our world today, machine learning has found applications in major domains such as business, entertainment, health and so on. Adequate understanding and knowledge are inevitable in order to bring out the most of these machine learning techniques. In our work, we have studied and applied popular...
Optimisation of laser welding of deep drawing steel for automotive applications by Machine Learning: A comparison of different techniques Literature often resorts to supervised Machine Learning approaches. However, selecting the ApTest method is non‐trivial and often decision making relies on ... G Ma...
Fundamental period of masonry-infill reinforced concrete frame structures was predicted usingexplainablemachine learning (ANN, SVR, RF, and KNN)Explainable artificial intelligence (XAI) methods reveal the causality of predictions and models' inner working, improving end-users' trust in machine learning.LI...
aIn classification problems, many different active learning techniques are often adopted to find the most informative samples for labeling in order to save human labors. Among them, active learning support vector machine (SVM) is one of the most representative approaches, in which model parameter is...
Machine Learning Techniques (MLT)Neural Networks (NN)Case Based Reasoning (CBR)Classification and Regression Trees (Cart)Rule InductionMachine learning framework adequately "realizes" how to evaluate from preparing set of finished undertakings. The principle objective and commitment oGoyal, Yojana...
This integration of data processing and machine learning techniques can offer many other interesting applications for SAGD production. But it may also have a limitation in parameters and data sources. In the future, more complex SAGD conditions and real field data will be considered to study more ...
The in situ techniques can measure ET accurately but the observations have limited spatial and temporal coverage. Modeling approaches have been used to estimate ET at broad spatial and temporal scales, while accurately simulating ET at regional scales remains a major challenge. In this study, we ...