A5100429001- Advanced Multi-Objective Optimization Algorithms
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Differential Equations and Numerical Methods
- Topology Optimization in Engineering
- Probabilistic and Robust Engineering Design
- Fractional Differential Equations Solutions
- Stellar, planetary, and galactic studies
- Astro and Planetary Science
- Data Management and Algorithms
- Reservoir Engineering and Simulation Methods
- Blockchain Technology Applications and Security
- Smart Grid Security and Resilience
- Hydrocarbon exploration and reservoir analysis
- Nonlinear Differential Equations Analysis
- Vehicle Routing Optimization Methods
- Energy Efficient Wireless Sensor Networks
- Underwater Vehicles and Communication Systems
- Numerical Methods and Algorithms
- Network Security and Intrusion Detection
- Mental Health via Writing
- Optimal Experimental Design Methods
- Robotic Path Planning Algorithms
- Water resources management and optimization
- Graph Theory and Algorithms
Qingdao University of Science and Technology
2025
Guangxi University of Science and Technology
2024
University of Science and Technology Beijing
2024
Beijing Microelectronics Technology Institute
2023
Shanghai Ocean University
2022-2023
King's College London
2023
Northeastern University
2023
University of Electronic Science and Technology of China
2022
Chinese Academy of Medical Sciences & Peking Union Medical College
2022
North China University of Technology
2022
Most existing multiobjective evolutionary algorithms experience difficulties in solving many-objective optimization problems due to their incapability balance convergence and diversity the high-dimensional objective space. In this paper, we propose a novel algorithm using one-by-one selection strategy. The main idea is that environmental selection, offspring individuals are selected one by based on computationally efficient indicator increase pressure toward Pareto optimal front. once an...
Interval many-objective optimization problems (IMaOPs), involving more than three objectives and at least one subjected to interval uncertainty, are ubiquitous in real-world applications. However, there have been very few effective methods for solving these problems. In this paper, we proposed a set-based genetic algorithm effectively solve them. The original problem was first transformed into deterministic bi-objective problem, where new hyper-volume imprecision. A Pareto dominance relation...
One of the most important and widely faced optimization problems in real applications is interval multiobjective (IMOPs). The state-of-the-art evolutionary algorithms (EAs) for IMOPs (IMOEAs) need a great deal objective function evaluations to find final Pareto front with good convergence even distribution. Further, uncertainty. In this paper, we incorporate several local searches into an existing IMOEA, propose memetic algorithm (MA) tackle IMOPs. At start, IMOEA utilized explore entire...
Abstract In this paper, we consider a state estimation problem. problem, sensor measures the of linear discrete‐time system and sends measurements to an estimator via packet‐dropping communication link. We are concerned with effect Denial‐of‐Service (DoS) attacks on stability system, particularly focus how examine whether channel is under DoS attack or not as well defend accordingly, if defense possible. formulate detection problem hypothesis testing provided that statistics known priori ....
The burgeoning field of Digital Humanities has experienced remarkable growth, catalyzed by advances in computing technology and the increasing digitization cultural artifacts. This paper delves into dynamic interplay between digital humanities artificially intelligent generated content (AIGC), exploring their intersection transformative potential. Through a comprehensive literature review, we highlight multifaceted landscape surrounding AIGC, including biases, ethical considerations,...
Desert encroachment significantly threatens the living and activity space of humanity, undertaking human-directed vegetation restoration is one effective ways to prevent desert expansion. In process restoration, counting number tree saplings for rapidly assessing survival rate (such as Haloxylon ammodendron) a critical task within process. However, traditional ground-based statistical methods are resource-intensive time-consuming. This paper proposed novel unsupervised fine segmentation...
In some real-world optimization problems, the parameters of an objective function may be expressed as intervals, such benefit a project and driving speed robot. An problem involving interval multiple conflicting objectives is termed multiobjective with (IMOP). Few studies have addressed IMOPs compared to deterministic at present. addition, uncertainty involved in problems raises higher demands on diversity efficiency algorithm. Therefore, adaptive reference vector-based evolutionary...
Collaborative filtering-based recommender systems that rely on a single type of behavior often encounter serious sparsity issues in real-world applications, leading to unsatisfactory performance. Multi-behavior Recommendation (MBR) is method seeks learn user preferences, represented as vector embeddings, from auxiliary information. By leveraging these preferences for target recommendations, MBR addresses the problem and improves accuracy recommendations. In this paper, we propose MB-HGCN,...
In modern urban areas, we often find a transportation network that follows superimposed pattern. this paper, propose novel method to generate virtual traffic based on (1) image-derived templates, and (2) rule-based generating system. Using 2D images as input maps, various road maps with different patterns could be produced. This model adjusts itself intelligently in order avoid restricted geographical areas or developments. The generative closely directions of elevation connects ends ways...