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南京工业大学 国内
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吴 斌
教授、硕士生导师
经济与管理学院
电子邮件
seasimen
aliyun
com
网站
https://jgy.njtech.edu.cn/info/1023/4672.htm
h-index
445
引用
9
H-指数
根据储存在 Pure 的刊物以及来自 Scopus 的引用文献数量计算
2008
2025
每年的科研成果
综述
指纹
网络
科研成果
(30)
相似简介
(1)
指纹
深入其中 Bin Wu 为活跃的研究主题。这些主题标签来自此人的成果。它们共同形成唯一的指纹。
分类
加权
按字母排序
Computer Science
Artificial Bee Colony Algorithm
100%
Vehicle Routing
62%
Historical Knowledge
50%
Historical Information
50%
Local Optimization
50%
Technical Support
50%
Unique Solution
50%
Non-Dominated Sorting Genetic Algorithm II
50%
Differential Evolution
50%
Scheduling Problem
50%
Dynamic Network
50%
Customer Satisfaction
50%
Feature Selection
50%
Hyperspectral Image
50%
Objective Feature
50%
Supply Chain
50%
Contract Model
50%
Harmony Search
50%
Global Optimization
50%
Reference Point
50%
Optimization Problem
50%
Digital Twin
50%
Artificial Bee Colony
50%
Nave Bayes
50%
Deep Reinforcement Learning
50%
Job Shop Scheduling Problem
50%
Memetic Algorithm
50%
Bin Packing Problem
37%
Band Selection
33%
Search Mechanism
33%
Disaster Relief
33%
Feasible Solution
33%
Automated Guided Vehicle
33%
Deep Q-Network
33%
Equilibrium Point
25%
Digital Twin Technology
25%
Local Search Method
25%
Resource Limitation
25%
Computing Resource
25%
Combined Effect
25%
Resource Requirement
25%
Computational Experiment
25%
Benchmark Instance
25%
Local Search Algorithm
25%
Iteration Process
25%
Candidate Solution
25%
Search Neighborhood
25%
Hybrid Algorithm
20%
Performance Optimization
16%
Search Experience
16%
Engineering
Routing Problem
100%
Search Strategy
66%
Q-Learning
50%
Customer Satisfaction
50%
Optimisation Problem
50%
Computer Simulation
50%
Hydrophilicity
50%
Learning System
50%
Desalination
50%
Reverse Osmosis Membrane
33%
Local Search
33%
Initial Population
33%
Model Problem
25%
Mode Control
25%
Iteration Process
25%
Search Neighborhood
25%
Decoding Technique
25%
Pareto Frontier
25%
Critical Path
25%
Automatic Machine
25%
Intelligent Transportation
16%
Engineering
16%
Simulation Result
16%
Population Increase
16%
Discrete Value
16%
Search Space
16%
Interrelationship
16%
Individual Aspect
16%
Mean Value
16%
Optimal Condition
16%
Molecular Level
16%
Pressure Drop
16%
Machine Learning Method
16%
Encoding Method
12%
Real Number
12%
Time Dependent Network
12%
Adaptive Inertia Weight
12%
Customer Experience
12%
Construction Planning
10%
Peak Period
10%
