A5028303789- Metaheuristic Optimization Algorithms Research
- Advanced Optimization Algorithms Research
- Advanced Multi-Objective Optimization Algorithms
- Advanced Control Systems Optimization
- Evolutionary Algorithms and Applications
- Advanced Algorithms and Applications
- Advanced Image and Video Retrieval Techniques
- Neural Networks and Applications
- Image Retrieval and Classification Techniques
- Face and Expression Recognition
- Matrix Theory and Algorithms
- Optimization and Variational Analysis
- Iterative Methods for Nonlinear Equations
- Sparse and Compressive Sensing Techniques
- Fault Detection and Control Systems
- Artificial Intelligence in Games
- Data-Driven Disease Surveillance
- Artificial Intelligence in Healthcare
- Advanced Bandit Algorithms Research
- Fractional Differential Equations Solutions
- Educational Technology and Assessment
- EEG and Brain-Computer Interfaces
- Multi-Criteria Decision Making
- Scheduling and Optimization Algorithms
- Scheduling and Timetabling Solutions
Dongguan University of Technology
2014-2024
Henan Polytechnic University
2019
Central South University
2019
Hunan University
2010-2011
Several stability analyses and stable regions of particle swarm optimization (PSO) have been proposed before. The assumption stagnation different definitions are adopted in these analyses. In this paper, the order-2 PSO is analyzed based on a weak assumption. A new definition an region obtained. existing for canonical compared, especially their corresponding regions. It shown that classical too strict not necessary. Moreover, among all stability, it our requires weakest conditions,...
The popular performance profiles and data for benchmarking deterministic optimization algorithms are extended to benchmark stochastic global problems. A general confidence interval is employed replace the significance test, which in traditional methods but suffering more criticisms. Through computing bounds of visualizing them with (or) profiles, our method can be used compare by graphs. Compared methods, synthetic statistically therefore suitable large sets some sample-mean-based e.g.,...
Image similarity measurement is a fundamental problem in the field of computer vision. It widely used image classification, object detection, retrieval, and other fields, mostly through Siamese or triplet networks. These networks consist two three identical branches convolutional neural network (CNN) share their weights to obtain high-level feature representations so that similar images are mapped close each space, dissimilar pairs far from other. Especially, known as state-of-the-art method...
MATLAB <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> has built in five derivative-free optimizers (DFOs), including two direct search algorithms (simplex search, pattern search) and three heuristic (simulated annealing, particle swarm optimization, genetic algorithm), plus a few the official user repository, such as Powell's conjugate (PC) recommended by MathWorks . To help practicing engineer or scientist to choose DFO most suitable...
Numerical comparison is often key to verifying the performance of optimization algorithms, especially, global algorithms. However, studies have so far neglected issues concerning strategies necessary rank algorithms properly. To fill this gap for first time, we combine voting theory and numerical research areas, which been disjoint far, thus extend results former latter In particular, investigate compatibility arising from comparing two more than termed "C2" "C2+" in article, respectively....
Through modeling human's brainstorming process, the brain storm optimization (BSO) algorithm has become a promising population-based evolutionary algorithm. However, BSO is pointed out that it possesses degenerated L-curve phenomenon, i.e., often gets near optimum quickly but needs much more cost to improve accuracy. To overcome this question in paper, an excellent direct search-based local solver, Nelder–Mead Simplex method adopted BSO. combining BSO's exploration ability and NMS's...
Numerical comparison serves as a major tool in evaluating the performance of optimization algorithms, especially nondeterministic but existing methods may suffer from 'cycle ranking' paradox and/or 'survival non-fittest' paradox. This paper searches for paradox-free data analysis numerical comparison. It is discovered that class sufficient conditions exist designing analysis. Rigorous modeling and deduction are applied to profile employing filter. thus further proven algorithm-independent...
This paper proposed a recommendation model called RM-SA, which is based on multi-emotional analysis in networks. In the RM-MES scheme, values of goods are primarily derived from probabilities calculated by similar existing system during initiation stage system. First, behaviors those users can be divided into three aspects, including browsing goods, buying only, and purchasing–evaluating goods. Then, characteristics emotional information user considered to determine similarities between...