results of damage prediction in buildings can be used as a useful tool for managing and decreasing seismic risk of earthquakes. in this study, damage spectrum and c4.5 decision tree algorithm were utilized for damage prediction in steel buildings during earthquakes. in order to prepare the damage spectrum, steel buildings were modeled as a single-degree-of-freedom (sdof) system and time-history...

This study compares the Accuracy of Support Vector Machine (SVM) Classifier and Decision Tree (DT) in predicting Innovative Bradycardia disease diagnosis. Materials Methods: There are 7,500 records dataset that was used for this investigation. 40 utilized test to get a 95% confidence level 1% margin error. 12 qualities or features per record. Using SVM, is detected. Results: According statistic...

This research analyzed different aspects of coronavirus disease (COVID-19) for patients who have coronavirus, find out which an effect to patient death. First, a literature has been made with the previous that done on analysis dataset using Machine learning (ML) algorithm. Second, data analytics is applied Sulaymaniyah, Iraq, factors affect mortality rate patients. Third, classification algorit...

This paper presents a particle swarm optimization (PSO)-based fuzzy expert system for the diagnosis of coronary artery disease (CAD). The designed system is based on the Cleveland and Hungarian Heart Disease datasets. Since the datasets consist of many input attributes, decision tree (DT) was used to unravel the attributes that contribute towards the diagnosis. The output of the DT was converte...

Many decision tree (DT) induction algorithms, including the popular C4.5 family, are based on the Conditional Entropy (CE) measure family. An interesting question involves the relative performance of other entropy measure families such as Class-Attribute Mutual Information (CAMI). We therefore conducted a theoretical analysis of the CAMI family that enabled us to expose relationships with CE an...

This paper illustrates the application of evolutionary algorithms (EAs) to the problem of oblique decision-tree (DT) induction. The objectives are to demonstrate that EAs can find classifiers whose accuracy is competitive with other oblique tree construction methods, and that, at least in some cases, this can be accomplished in a shorter time. We performed experiments with a (1+1) evolution str...

The drinking and irrigation water scarcity is a major global issue, particularly in arid semi-arid zones. In rural areas, groundwater could be used as an alternative additional supply source order to reduce human suffering terms of scarcity. this context, the purpose present study facilitate potentiality mapping via spatial-modelling techniques, individual ensemble machine-learning models. Rand...

This paper presents a decision support tool for promoters/investors of geothermal energy projects, based on tree (DT) structure. The DT aims to assist stakeholders select public engagement strategies, alternative financing solutions and risk mitigation measures (or options) projects. Public is necessary the successful development operation Available studies (including toolkits protocols) common...

It is necessary to develop an explainable model clarify how and why a medical makes particular decision. Local posthoc AI (XAI) techniques, such as SHAP LIME, interpret classification system predictions by displaying the most important features rules underlying any prediction locally. Therefore, in order compare two or more XAI methods, they must first be evaluated qualitatively quantitatively....