Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran
TLDR
In this article, water resources management in watersheds are managed under varying shares of water balance under different climatic conditions, and its correct prediction poses a significant challenge before water resource management.Abstract:
Evaporation accounts for varying shares of water balance under different climatic conditions, and its correct prediction poses a significant challenge before water resources management in watershed...read more
Citations
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A review on exploration of Fe2O3 photocatalyst towards degradation of dyes and organic contaminants
C.N.C. Hitam,Aishah Abdul Jalil +1 more
TL;DR: The present review thoroughly summarized the classification, synthesis route of Fe 2O3 with different morphologies, and several modifications of Fe2O3 for improved photocatalytic performance, including the incorporation with supporting materials, formation of heterojunction with other semiconductors, as well as the fabrication of Z-scheme.
Journal ArticleDOI
A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU
Sweta Bhattacharya,Siva Rama Krishnan S,Praveen Kumar Reddy Maddikunta,Rajesh Kaluri,Saurabh Singh,Thippa Reddy Gadekallu,Mamoun Alazab,Usman Tariq +7 more
TL;DR: A hybrid principal component analysis (PCA)-firefly based machine learning model to classify intrusion detection system (IDS) datasets and experimental results confirm the fact that the proposed model performs better than the existing machine learning models.
Journal ArticleDOI
Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm
Babak Mohammadi,Saeid Mehdizadeh +1 more
TL;DR: In this paper, support vector regression (SVR) was applied to the modeling of daily evapotranspiration (ET0) at three meteorological stations in Iran subject to different climates: Isfahan (arid), Urmia (semi-arid) and Yazd (hyperarid). Different preprocessing approaches [relief (RL), random forests (RF), principal component analysis (PCA), and Pearson's correlation (COR)] served to determine the SVR's optimal input combinations.
Journal ArticleDOI
Spatiotemporal Modeling for Nonlinear Distributed Thermal Processes Based on KL Decomposition, MLP and LSTM Network
TL;DR: A spatiotemporal model based on the Karhunen-Loève decomposition, the multilayer perceptron (MLP), and the long short-term memory (L STM) network, named KL-MLP-LSTM, is developed for estimating temperature distributions with a three-step procedure.
References
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Journal ArticleDOI
Summarizing multiple aspects of model performance in a single diagram
TL;DR: In this article, a diagram has been devised that can provide a concise statistical summary of how well patterns match each other in terms of their correlation, their root-mean-square difference, and the ratio of their variances.
Book ChapterDOI
Firefly algorithms for multimodal optimization
TL;DR: In this article, a new Firefly Algorithm (FA) was proposed for multimodal optimization applications. And the proposed FA was compared with other metaheuristic algorithms such as particle swarm optimization (PSO).
Journal ArticleDOI
Firefly algorithm: recent advances and applications
Xin-She Yang,Xingshi He +1 more
TL;DR: It is concluded that metaheuristics such as firefly algorithm are better than the optimal intermittent search strategy and their implications for higherdimensional optimisation problems.
Journal ArticleDOI
Estimating Evapotranspiration using Artificial Neural Network
Manoranjan Kumar,Narendra Singh Raghuwanshi,Rajendra Singh,Wesley W. Wallender,William O. Pruitt +4 more
TL;DR: This study investigates the utility of artificial neural networks (ANNs) for estimation of daily grass reference crop evapotranspiration (ETo) and compares the performance of ANNs with the conventional method (Penman–Monteith) used to estimate ETo.
Journal ArticleDOI
A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
TL;DR: In this article, two nonlinear time-series models for predicting groundwater level (GWL) fluctuations using artificial neural networks (ANNs) and support vector machines (SVMs) were developed.
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