Groundwater Potential Mapping Using GIS-Based Hybrid Artificial Intelligence Methods.

Groundwater is one of the major valuable water resources for the use of communities, agriculture, and industries. In the present study, we have developed three novel hybrid artificial intelligence (AI) models which is a combination of modified RealAdaBoost (MRAB), bagging (BA), and rotation forest (RF) ensembles with functional tree (FT) base classifier for the groundwater potential mapping (GPM) in the basaltic terrain at DakLak province, Highland Centre, Vietnam. Based on the literature survey, these proposed hybrid AI models are new and have not been used in the GPM of an area.

Human development index in a context of human development: Review on the western Balkans countries.

Introduction: The Human Development Index (HDI), as one of the more complex composite indicators of the level of human potential and quality of life, is a combination of three dimensions (indicators, factors): life expectancy at birth, the middle number of years of education and the expected number of years of schooling combined into a single education index and economic benefits expressed by production, or GDP (gross domestic product) according to purchasing power (PPP US $).

Methods: The same measures and average achievements in the field of health, education, and living standards are presented. The HDI was first developed in 1990 under the United Nations Development Program (UNDP) and is published as Human Development Reports (HDR).

Removal performance and optimisation of pharmaceutical micropollutants from synthetic domestic wastewater by hybrid treatment.

Occurrence of pharmaceutical micropollutants in aquatic environments has been one amongst serious environmental problems. During this study, two reactors, including a sequencing batch reactor (SBR) + powdered composite adsorbent (CA) (first reactor, SBR + CA) and a sequencing batch reactor (second reactor, SBR), were designed to treat synthetic wastewater. Powdered CA was added with a dosage of 4.

Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam.

The main aim of this study is to assess groundwater potential of the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) ensemble technique. For this study, twelve conditioning factors and wells yield data was used to create the training and testing datasets for the development and validation of the ensemble RABANN model. Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and several statistical performance measures were used to validate and compare performance of the ensemble RABANN model with the single ANN model.

Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis.

In this study, we developed Different Artificial Intelligence (AI) models namely Artificial Neural Network (ANN), Adaptive Network based Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM) for the prediction of Compression Coefficient of soil (Cc) which is one of the most important geotechnical parameters. A Monte Carlo approach was used for the sensitivity analysis of the AI models and input parameters. For the construction and validation of the models, 189 soft clayey soil samples were analyzed.