Modelling the energy performance of residential buildings using advanced computational frameworks based on RVM, GMDH, ANFIS-BBO and ANFIS-IPSO

A Combination of Feature Selection and Random Forest Techniques to Solve a Problem Related to Blast-Induced Ground Vibration

(2020) Zhang et al.   Applied Sciences-Basel

Improved prediction of slope stability using a hybrid stacking ensemble method based on finite element analysis and field data

(2020) Navid Kardani et al.   Journal of Rock Mechanics and Geotechnical Engineering

Phase behavior modeling of asphaltene precipitation utilizing RBF-ANN approach

(2019) Mohammad Navid Kardani et al.   PETROLEUM SCIENCE AND TECHNOLOGY

Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility

(2019) Abolfazl Jaafari et al.   CATENA

Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimization

(2019) Wei Chen et al.   JOURNAL OF HYDROLOGY

Tuning machine learning models for prediction of building energy loads

(2019) Saleh Seyedzadeh et al.   Sustainable Cities and Society

Evaluation of soil liquefaction using AI technology incorporating a coupled ENN / t-SNE model

(2019) Pierre Guy Atangana Njock et al.   SOIL DYNAMICS AND EARTHQUAKE ENGINEERING

Group contribution methods for estimating CO2 absorption capacities of imidazolium and ammonium-based polyionic liquids

(2018) Mohammad Navid Kardani et al.   JOURNAL OF CLEANER PRODUCTION

Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane City

(2017) Ravinesh C. Deo et al.   JOURNAL OF HYDROLOGIC ENGINEERING

Utilization of LSSVM strategy to predict water content of sweet natural gas

(2017) Mohammad Navid Kardani et al.   PETROLEUM SCIENCE AND TECHNOLOGY

Application of neural networks for evaluating energy performance certificates of residential buildings

(2016) Fazel Khayatian et al.   ENERGY AND BUILDINGS

Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks

(2016) Chirag Deb et al.   ENERGY AND BUILDINGS

Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm

(2016) Sasan Barak et al.   INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS

Hourly prediction of a building's electricity consumption using case-based reasoning, artificial neural networks and principal component analysis

(2015) Radu Platon et al.   ENERGY AND BUILDINGS

Building's electricity consumption prediction using optimized artificial neural networks and principal component analysis

(2015) Kangji Li et al.   ENERGY AND BUILDINGS

Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models

(2015) Ravinesh C. Deo et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

A prediction model based on neural networks for the energy consumption of a bioclimatic building

(2014) R. Mena et al.   ENERGY AND BUILDINGS

Spatial variability of rock depth using adaptive neuro-fuzzy inference system (ANFIS) and multivariate adaptive regression spline (MARS)

(2014) Pijush Samui et al.   Environmental Earth Sciences

Fused deposition modelling (FDM) process parameter prediction and optimization using group method for data handling (GMDH) and differential evolution (DE)

(2014) Farzad Rayegani et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Prediction of compressive strength of self-compacting concrete using least square support vector machine and relevance vector machine

(2014) Bhairevi Ganesh Aiyer et al.   KSCE Journal of Civil Engineering

Improved benchmarking comparability for energy consumption in schools

(2013) Sung-Min Hong et al.   BUILDING RESEARCH AND INFORMATION

Accurate quantitative estimation of energy performance of residential buildings using statistical machine learning tools

(2012) Athanasios Tsanas et al.   ENERGY AND BUILDINGS

Utilization relevance vector machine for slope reliability analysis

(2011) Pijush Samui et al.   APPLIED SOFT COMPUTING

Application of support vector machine and relevance vector machine to determine evaporative losses in reservoirs

(2011) Pijush Samui et al.   HYDROLOGICAL PROCESSES

Least square support vector machine and relevance vector machine for evaluating seismic liquefaction potential using SPT

(2011) Pijush Samui   NATURAL HAZARDS

A decision tree method for building energy demand modeling

(2010) Zhun Yu et al.   ENERGY AND BUILDINGS

Adaptive HVAC zone modeling for sustainable buildings

(2009) Glenn Platt et al.   ENERGY AND BUILDINGS

Development of Artificial Neural Network based heat convection algorithm for thermal simulation of large rectangular cross-sectional area Earth-to-Air Heat Exchangers

(2009) Jian Zhang et al.   ENERGY AND BUILDINGS

China building energy consumption: Situation, challenges and corresponding measures

(2009) W.G. Cai et al.   ENERGY POLICY

Biogeography-Based Optimization for Different Economic Load Dispatch Problems

(2009) Aniruddha Bhattacharya et al.   IEEE TRANSACTIONS ON POWER SYSTEMS

Development and validation of regression models to predict monthly heating demand for residential buildings

(2008) Tiberiu Catalina et al.   ENERGY AND BUILDINGS

Prediction of energy demands using neural network with model identification by global optimization

(2008) Ryohei Yokoyama et al.   ENERGY CONVERSION AND MANAGEMENT

Biogeography-Based Optimization

(2008) D. Simon   IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION

An applied artificial intelligence approach towards assessing building performance simulation tools

(2007) Abraham Yezioro et al.   ENERGY AND BUILDINGS

A review on buildings energy consumption information

(2007) Luis Pérez-Lombard et al.   ENERGY AND BUILDINGS

Contrasting the capabilities of building energy performance simulation programs

(2006) Drury B. Crawley et al.   BUILDING AND ENVIRONMENT