Jie Wang

Management Science and Operations Research · with Wang · 2015–2017

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Management Science and Operations Research — 21 citations into it; #4,336 of 11,946 by trust here, #5,316 by citations
• Economics and Econometrics — 16 citations into it; #9,158 of 23,481 by trust here, #14,996 by citations
• Artificial Intelligence — 14 citations into it; #19,294 of 35,345 by trust here, #27,551 by citations
• Electrical and Electronic Engineering — 6 citations into it

Whom Jie Wang trusts overall

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

1. Spyros Makridakis
2. Dennis Olson
3. David E. Rumelhart
4. J. Wang
5. Manoochehr Ghiassi
6. Arash Bahrammirzaee
7. Ruey S. Tsay
8. Durdu Ömer Faruk
9. Kyoung-jae Kim
10. Xavier Gabaix

Who trusts Jie Wang overall

1. Weiwei Jiang
2. Ehsan Hoseinzade
3. Yanhui Chen
4. Saman Haratizadeh
5. Spyros Makridakis
6. Kaijian He
7. Geoffrey Kwok Fai Tso
8. Hamed Ghoddusi

Papers from Jie Wang's perspective

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

1. A hybrid genetic-neural architecture for stock indexes forecasting
2. Adaptive Neural Output Feedback Tracking Control for a Class of Uncertain Discrete-Time Nonlinear Systems (IEEE Transactions on Neural Networks)
3. Parallel Distributed Processing: Explorations in the Micro-structure of Cognition
4. Neural network forecasts of Canadian stock returns using accounting ratios
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Finding Structure in Time
7. Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
8. Pattern Recognition and Machine Learning
9. Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root?
10. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper

Their papers

• Forecasting stochastic neural network based on financial empirical mode decomposition (2017) — 95 citations
• Forecasting energy market indices with recurrent neural networks: Case study of crude oil price fluctuations (2016) — 132 citations
• Forecasting stock market indexes using principle component analysis and stochastic time effective neural networks (2015) — 148 citations