Survey of computational intelligence as basis to big flood management: challenges, research directions and future work
Farnaz Fotovatikhah,Manuel Herrera,Shahaboddin Shamshirband,Kwok Wing Chau,Sina Ardabili,Md. Jalil Piran +5 more
TLDR
This paper aims to present a comprehensive survey about the application of CI-based methods in FMSs and identifies and introduces the most promising approaches nowadays with respect to the accuracy and error rate for flood debris forecasting and management.Abstract:
Flooding produces debris and waste including liquids, dead animal bodies and hazardous materials such as hospital waste. Debris causes serious threats to people’s health and can even block the road...read more
Citations
More filters
Journal ArticleDOI
An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction
TL;DR: The obtained results reveal that the EELM model is a robust expert model and can be embraced practically in real-life water resources management and river sustainability decisions.
Journal ArticleDOI
Flood prediction using machine learning models: Literature review
TL;DR: In this paper, the state-of-the-art machine learning models for both long-term and short-term floods are evaluated and compared using a qualitative analysis of robustness, accuracy, effectiveness and speed.
Journal ArticleDOI
State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
Amir Mosavi,Amir Mosavi,Amir Mosavi,Mohsen Salimi,Sina Ardabili,Timon Rabczuk,Shahaboddin Shamshirband,Annamária R. Várkonyi-Kóczy +7 more
TL;DR: There is an outstanding rise in the accuracy, robustness, precision and generalization ability of the ML models in energy systems using hybrid ML models.
Journal ArticleDOI
COVID-19 outbreak prediction with machine learning
Sina Ardabili,Amir Mosavi,Pedram Ghamisi,Filip Ferdinand,Annamária R. Várkonyi-Kóczy,Uwe Reuter,Timon Rabczuk,Peter M. Atkinson +7 more
TL;DR: A comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to susceptible–infected–recovered (SIR) and susceptible-exposed-infectious-removed (SEIR) models suggests machine learning as an effective tool to model the outbreak.
Journal ArticleDOI
Flood Prediction Using Machine Learning Models: Literature Review
TL;DR: In this paper, the state of the art of ML models in flood prediction and to give insight into the most suitable models are presented. And the major trends in improving the quality of the flood prediction models are investigated.
References
More filters
Journal ArticleDOI
Differential Evolution – A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces
Rainer Storn,Kenneth Price +1 more
TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Book
Data Mining: Concepts and Techniques
TL;DR: This book presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects, and provides a comprehensive, practical look at the concepts and techniques you need to get the most out of real business data.
Book
Pattern Recognition with Fuzzy Objective Function Algorithms
TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.
Journal ArticleDOI
Deep learning in neural networks
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Related Papers (5)
Rainfall–runoff modeling using artificial neural network coupled with singular spectrum analysis
C.L. Wu,C.L. Wu,Kwok Wing Chau +2 more