D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 48 Citations 9,372 296 World Ranking 4032 National Ranking 103

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Abbas Khosravi focuses on Artificial neural network, Prediction interval, Artificial intelligence, Mathematical optimization and Coverage probability. His work carried out in the field of Artificial neural network brings together such families of science as Nonparametric statistics, Particle swarm optimization and Data mining. His Prediction interval research integrates issues from Econometrics and Minification.

His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition. His work in the fields of Mathematical optimization, such as Probabilistic-based design optimization and Optimization problem, overlaps with other areas such as Electric power system, Wind power forecasting and AC power. His Electric power system research includes themes of Electrical load and Solar power.

His most cited work include:

  • A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings (356 citations)
  • Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals (334 citations)
  • Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals (306 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Artificial intelligence, Artificial neural network, Machine learning, Prediction interval and Mathematical optimization. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Genetic algorithm and Pattern recognition. His Artificial neural network research includes elements of Data mining, Control theory, Control theory, Uncertainty quantification and Algorithm.

His work carried out in the field of Machine learning brings together such families of science as Fuzzy logic and Bayesian inference. His research investigates the connection with Prediction interval and areas like Simulated annealing which intersect with concerns in Minification. His work on Particle swarm optimization as part of general Mathematical optimization study is frequently linked to Electric power system, bridging the gap between disciplines.

He most often published in these fields:

  • Artificial intelligence (44.48%)
  • Artificial neural network (41.28%)
  • Machine learning (27.05%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (44.48%)
  • Artificial neural network (41.28%)
  • Machine learning (27.05%)

In recent papers he was focusing on the following fields of study:

Abbas Khosravi mainly focuses on Artificial intelligence, Artificial neural network, Machine learning, Deep learning and Uncertainty quantification. His biological study spans a wide range of topics, including Field and Pattern recognition. He interconnects Mathematical optimization, Teleoperation, Transfer of learning, Algorithm and Training in the investigation of issues within Artificial neural network.

Mathematical optimization is frequently linked to Prediction interval in his study. His Prediction interval study combines topics in areas such as Econometrics and Realization. His work on Ensemble learning and Hyperparameter as part of general Machine learning research is often related to Noise and Data type, thus linking different fields of science.

Between 2019 and 2021, his most popular works were:

  • Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review (40 citations)
  • Deep imitation learning for autonomous vehicles based on convolutional neural networks (31 citations)
  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges (16 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Statistics

Abbas Khosravi mainly investigates Artificial intelligence, Machine learning, Deep learning, Artificial neural network and Feature extraction. His Artificial intelligence research incorporates elements of Field and Pattern recognition. His study in the field of Uncertainty quantification is also linked to topics like Functional near-infrared spectroscopy, Resting state fMRI and Visual perception.

His Uncertainty quantification research incorporates themes from Adversarial system, Wind speed, Training and Fuzzy logic. Abbas Khosravi has included themes like Virus and Disease markers in his Deep learning study. Abbas Khosravi studies Multilayer perceptron which is a part of Artificial neural network.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Muhammad Qamar Raza;Muhammad Qamar Raza;Abbas Khosravi.
Renewable & Sustainable Energy Reviews (2015)

703 Citations

Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

Hao Quan;Dipti Srinivasan;Abbas Khosravi.
IEEE Transactions on Neural Networks (2014)

536 Citations

Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals

A Khosravi;S Nahavandi;D Creighton;A F Atiya.
IEEE Transactions on Neural Networks (2011)

495 Citations

Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances

A. Khosravi;S. Nahavandi;D. Creighton;A. F. Atiya.
IEEE Transactions on Neural Networks (2011)

489 Citations

Construction of Optimal Prediction Intervals for Load Forecasting Problems

Abbas Khosravi;Saeid Nahavandi;Doug Creighton.
IEEE Transactions on Power Systems (2010)

234 Citations

Prediction Intervals for Short-Term Wind Farm Power Generation Forecasts

A. Khosravi;S. Nahavandi;D. Creighton.
IEEE Transactions on Sustainable Energy (2013)

230 Citations

A New Fuzzy-Based Combined Prediction Interval for Wind Power Forecasting

Abdollah Kavousi-Fard;Abbas Khosravi;Saeid Nahavandi.
IEEE Transactions on Power Systems (2016)

208 Citations

Interval Type-2 Fuzzy Logic Systems for Load Forecasting: A Comparative Study

A. Khosravi;S. Nahavandi;D. Creighton;D. Srinivasan.
IEEE Transactions on Power Systems (2012)

189 Citations

Prediction Intervals to Account for Uncertainties in Travel Time Prediction

A Khosravi;E Mazloumi;S Nahavandi;D Creighton.
IEEE Transactions on Intelligent Transportation Systems (2011)

169 Citations

A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

Hao Quan;Dipti Srinivasan;Ashwin M. Khambadkone;Abbas Khosravi.
Applied Energy (2015)

169 Citations

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