求解最优停时问题的一种新方法（英文）.docx

文档介绍：该【求解最优停时问题的一种新方法（英文） 】是由【niuww】上传分享，文档一共【3】页，该文档可以免费在线阅读，需要了解更多关于【求解最优停时问题的一种新方法（英文） 】的内容，可以使用淘豆网的站内搜索功能，选择自己适合的文档，以下文字是截取该文章内的部分文字，如需要获得完整电子版，请下载此文档到您的设备，方便您编辑和打印。求解最优停时问题的一种新方法（英文）
Title: A novel approach to solving the optimization of parking decision problem
Abstract:
Parking is a critical and often challenging issue in urban areas. Optimal parking decision-making can significantly impact transportation efficiency, vehicle emissions, and overall user satisfaction. In this paper, we propose a novel approach to solve the optimization of parking decision problem. Traditional parking optimization models typically focus on finding the nearest or cheapest parking spot, disregarding various real-world constraints and dynamic factors. Our approach considers multidimensional factors such as user preferences, context-aware data, and real-time parking availability to make intelligent parking decisions. The proposed method aims to improve parking efficiency, reduce traffic congestion, and enhance the overall user experience.
1. Introduction
Background
Problem Statement
Objectives
Contribution
2. Literature Review
Traditional Approaches to Parking Optimization
Context-Aware Parking Solutions
Intelligent Systems for Parking Optimization
3. Methodology
Data Collection and Preprocessing
Feature Engineering
Decision-Making Algorithm
Real-time Parking Availability Integration
4. Proposed Model
User Preferences Integration
Context-Aware Factors
Real-Time Parking Availability
Multi-Objective Optimization Approach
5. Results and Discussion
Evaluation Metrics
Experimental Setup
Comparison with Existing Models
Analysis of Results
6. Case Study: Urban Area Parking Optimization
Data Collection
Model Implementation
Real-Time Testing and Evaluation
Simulation Results
7. Discussion
Strengths of the Proposed Model
Limitations and Challenges
Future Research Directions
8. Conclusion
Summary of Contributions
Implications and Potential Applications
Final Remarks
The proposed approach provides a comprehensive solution to the optimization of parking decision problems. By integrating user preferences, context-aware factors, and real-time parking availability, the model increases the efficiency and effectiveness of parking decisions. The case study in an urban area demonstrates the potential benefits of the proposed approach in reducing traffic congestion and improving overall user satisfaction. The limitations and challenges are also discussed, providing directions for future research in this area. Ultimately, this method contributes to the development of intelligent parking systems that can enhance transportation efficiency and alleviate parking-related issues in urban areas.