Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping

H Hong, P Tsangaratos, I Ilia, C Loupasakis… - Science of the total …, 2020 - Elsevier
The main objective of the current study was to present a methodological approach that
combines Information Theory, a neural network and meta-heuristic techniques so as to …

Hot water temperature prediction using a dynamic neural network for absorption chiller application in Indonesia

MI Alhamid, K Saito - Sustainable Energy Technologies and …, 2018 - Elsevier
Weather condition particularly for solar radiation and dry bulb temperature has important
role in absorption chiller performance. In this paper hot water temperature prediction in …

Modeling the spatial and temporal variability of precipitation in northwest Iran

M Arab Amiri, MS Mesgari - Atmosphere, 2017 - mdpi.com
Spatial and temporal variability analysis of precipitation is an important task in water
resources planning and management. This study aims to analyze the spatial and temporal …

Spatial and temporal monthly precipitation forecasting using wavelet transform and neural networks, Qara-Qum catchment, Iran

M Arab Amiri, Y Amerian, MS Mesgari - Arabian Journal of Geosciences, 2016 - Springer
This paper aims to provide a spatial and temporal analysis to prediction of monthly
precipitation data which are measured at irregularly spaced synoptic stations at discrete time …

Mean areal precipitation estimation: methods and issues

RSV Teegavarapu - Rainfall, 2022 - Elsevier
Mean areal precipitation (MAP) estimate continues to serve as one of the essential inputs to
lumped hydrologic simulation models. Accurate MAP estimates require error and gap-free …

Point-of-interest semantic tag completion in a global crowdsourced search-and-discovery database

N Lagos, S Ait-Mokhtar, I Calapodescu - ECAI 2020, 2020 - ebooks.iospress.nl
Applications that process Point-of-Interest data are omnipresent nowadays. They range from
digital maps to recommender systems for places to visit, and personal assistants. The …

Incorporating Spatial Information for Regionalization of Environmental Parameters in Machine Learning Models

M Ohmer, F Doll, T Liesch - Mathematical Geosciences, 2024 - Springer
Abstract Machine learning models have gained popularity for environmental variable
predictions due to their capacity to capture complex relationships and automate learning …

Spatial disaggregation of areal rainfall using two different artificial neural networks models

S Kim, VP Singh - Water, 2015 - mdpi.com
The objective of this study is to develop artificial neural network (ANN) models, including
multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial …

A new framework for geospatial site selection using artificial neural networks as decision rules: a case study on landfill sites

SKM Abujayyab, MAS Ahamad… - ISPRS Annals of …, 2015 - isprs-annals.copernicus.org
This paper briefly introduced the theory and framework of geospatial site selection (GSS)
and discussed the application and framework of artificial neural networks (ANNs). The …

Deep-learning GIS hybrid approach in precipitation modeling based on spatio-temporal variables in the coastal zone of Turkey

H Apaydin, MT Sattari - Climate Research, 2020 - int-res.com
It is clearly known that precipitation is essential for fauna and flora. Studies have shown that
location and temporal factors have an effect on precipitation. Accurate prediction of …