Shahaboddin Shamshirband

Artificial Intelligence · 2015–2019

A researcher in the Science corpus: 25 papers; trusts 44 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 142 citations into it; #24,696 of 35,345 by trust here, #7,310 by citations
• Global and Planetary Change — 51 citations into it; #8,654 of 10,225 by trust here, #5,787 by citations
• Renewable Energy, Sustainability and the Environment — 49 citations into it
• Environmental Engineering — 42 citations into it; #3,748 of 5,479 by trust here, #1,260 by citations
• Electrical and Electronic Engineering — 36 citations into it
• Computer Vision and Pattern Recognition — 31 citations into it
• Water Science and Technology — 31 citations into it
• Biomedical Engineering — 21 citations into it

Whom Shahaboddin Shamshirband trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Thorsten Joachims
2. Kasra Mohammadi
3. Vladimir Naumovich Vapnik
4. Shiliang Sun
5. Yuhai Wu
6. Srinivas Mukkamala
7. Ozgur Kisi
8. Vladimir Naumovich Vapni
9. G. Huang
10. Xin-She Yang

Who trusts Shahaboddin Shamshirband overall

1. Amir Mosavi
2. Babak Mohammadi
3. Muhammad Naveed Akhter
4. Kasra Mohammadi
5. Babak Jahani
6. Ravinesh C. Deo
7. Roozbeh Moazenzadeh
8. Pouya Aghelpour
9. Saad Mekhilef

Papers from Shahaboddin Shamshirband's perspective

Ordered by how strongly the researchers Shahaboddin Shamshirband trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation (2015) — 241 citations
• Potential of adaptive neuro-fuzzy system for prediction of daily global solar radiation by day of the year (2015) — 124 citations
• Modeling temperature-based oil-water relative permeability by integrating advanced intelligent models with grey wolf optimization: Application to thermal enhanced oil recovery processes (2019) — 59 citations
• State of the Art of Machine Learning Models in Energy Systems, a Systematic Review (2019) — 516 citations
• A Deep Learning Ensemble Approach for Diabetic Retinopathy Detection (2019) — 489 citations
• Sustainable Business Models: A Review (2019) — 539 citations
• Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method. (2019) — 304 citations
• Application of ANNs, ANFIS and RSM to estimating and optimizing the parameters that affect the yield and cost of biodiesel production (2018) — 136 citations
• Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran (2018) — 313 citations
• Survey of computational intelligence as basis to big flood management: challenges, research directions and future work (2018) — 327 citations
• Modeling interfacial tension in N2/n-alkane systems using corresponding state theory: Application to gas injection processes (2018) — 50 citations
• Machine Learning-Based Sentiment Analysis for Twitter Accounts (2018) — 403 citations
• Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications (2017) — 316 citations
• Application of firefly algorithm-based support vector machines for prediction of field capacity and permanent wilting point (2017) — 143 citations
• A combined support vector machine-wavelet transform model for prediction of sediment transport in sewer (2016) — 55 citations
• Determining the most important variables for diffuse solar radiation prediction using adaptive neuro-fuzzy methodology; case study: City of Kerman, Iran (2016) — 69 citations
• Particle swarm optimization-based radial basis function network for estimation of reference evapotranspiration (2016) — 48 citations
• Estimating the diffuse solar radiation using a coupled support vector machine–wavelet transform model (2016) — 113 citations
• Identifying the most significant input parameters for predicting global solar radiation using an ANFIS selection procedure (2016) — 86 citations
• RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution (2016) — 59 citations