Yong Zhang

Artificial Intelligence · Information Sciences · 2010–2020

A researcher in the Science corpus: 5 papers; trusts 36 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it; #22,586 of 35,345 by trust here, #20,836 by citations
• Computational Theory and Mathematics — 43 citations into it; #8,752 of 12,182 by trust here, #4,696 by citations
• Electrical and Electronic Engineering — 23 citations into it; #9,993 of 16,539 by trust here, #10,714 by citations
• Computer Vision and Pattern Recognition — 8 citations into it; #17,841 of 21,575 by trust here, #20,271 by citations
• Control and Systems Engineering — 6 citations into it
• Evaluation & Benchmarks — 6 citations into it

Whom Yong Zhang trusts overall

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

1. Kalyanmoy Deb
2. Lingfeng Wang
3. Carlos Artemio Coello Coello
4. Mohammad Ali Abido
5. James Kennedy
6. Saudi Arabia
7. Malabika Basu
8. Eckart Zitzler
9. Margarita Reyes-Sierra
10. Praveen Kumar Tripathi

Who trusts Yong Zhang overall

1. Abdolreza Hatamlou
2. Manh Duong Phung
3. Mehrdad Rostami
4. Quang Phuc Ha
5. Kamal Berahmand
6. Gwo-Ching Liao
7. Zhile Yang
8. Tansel Dökeroğlu

Papers from Yong Zhang's perspective

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

1. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results (Evolutionary Computation)
2. A fast and elitist multiobjective genetic algorithm: NSGA-II
3. Evolutionary Algorithms for Solving Multi-Objective Problems
4. Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy (Evolutionary Computation)
5. Comparison of algorithms that select features for pattern classifiers (Pattern Recognition)
6. Simulated Binary Crossover for Continuous Search Space
7. Feature selection based on rough sets and particle swarm optimization (Pattern Recognition Letters)
8. Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art
9. Genetic Algorithms in Search Optimization and Machine Learning
10. Analytical solution for combined economic and emissions dispatch

Their papers

• Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm (2010) — 196 citations
• Binary differential evolution with self-learning for multi-objective feature selection (2020) — 399 citations
• Robot path planning in uncertain environment using multi-objective particle swarm optimization (2013) — 391 citations
• A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch (2012) — 295 citations
• Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification (2017) — 314 citations