A5100353370- Additive Manufacturing and 3D Printing Technologies
- Manufacturing Process and Optimization
- Vehicle emissions and performance
- Transportation Planning and Optimization
- Autonomous Vehicle Technology and Safety
- Neural Networks and Applications
- Electric and Hybrid Vehicle Technologies
- Advanced Battery Technologies Research
- Thermochemical Biomass Conversion Processes
- biodegradable polymer synthesis and properties
- Electric Vehicles and Infrastructure
- Traffic and Road Safety
- Transportation and Mobility Innovations
- Data Stream Mining Techniques
- Bone Tissue Engineering Materials
- Innovations in Concrete and Construction Materials
- Stock Market Forecasting Methods
- Advanced Sensor and Energy Harvesting Materials
- Traffic control and management
- Advanced Theoretical and Applied Studies in Material Sciences and Geometry
- Air Quality Monitoring and Forecasting
- Atmospheric chemistry and aerosols
- Nanomaterials and Printing Technologies
Xi’an Jiaotong-Liverpool University
2024
Miami University
2022
Research Institute of Highway
2021
Ministry of Transport
2021
University of Michigan–Dearborn
2019
University of Michigan
2014
Energy optimization for plug-in hybrid electric vehicles (PHEVs) is a challenging problem due to the system complexity and many physical operational constraints in PHEVs. In this paper, we present Q-learning-based in-vehicle learning that free of models can robustly converge an optimal energy control solution. The proposed machine algorithms combine neuro-dynamic programming (NDP) with future trip information effectively estimate expected cost (expected cost-to-go) given vehicle state...
As a promising industrial thermoplastic polymer material, high-density polyethylene (HDPE) possesses distinct properties of ease to process, good biocompatibility, high recyclability, etc. and has been widely used make packaging, prostheses implants, liquid-permeable membranes. Traditional manufacturing processes for HDPE, including injection molding, thermoforming, rotational require molds or post processing. In addition, part shapes are highly restricted., Thus, fused deposition modeling...
In this paper, we present a new investment strategy for optimal gains on investments in the stock market. Neural Network (NN)-based framework is used trading prediction and forecasting. To end, statistical measures based return volatility are to filter out low performing sectors A simple but effective method price Simple Moving Averages (SMAs) measure given stock. The proposed NN-based system uses strongest indices market addition predicting decisions such as Buy or Sell, also aims at...
Inspired by microstructure characteristics of mantis shrimp propodus with high mechanical strength, the bionic continuous carbon fiber (CF) reinforced acrylonitrile butadiene styrene (ABS) resin composite layered spiral structure was prepared successfully via self-built integration 3D printing. Combined printing demands ABS resin, model divided into 10 layers cylindrical entities which spiralled from 0° to 45°. The printed fibers realized designed specific arrangement direction in matrix,...
Abstract Owing to its superior durability, good biocompatibility, and high recycling capability, high-density polyethylene (HDPE) has been widely applied into making prosthetic implants, liquid permeable membranes, corrosion-resistant pipes, etc., gains popularity in packaging, consumer goods, chemical industries. Injection molding blow are two most common conventional processes of HDPE products. These processes, however, considered time-consuming labor-intensive since molds usually needed...
Big data has shown its uniquely powerful ability to reveal, model, and understand driver behaviors. The amount of affects the experiment cost conclusions in analysis. Insufficient may lead inaccurate models while excessive waste resources. For projects that millions dollars, it is critical determine right needed. However, how decide appropriate not been fully studied realm This paper systematically investigates this issue estimate much naturalistic driving (NDD) needed for understanding...
Traffic safety and pollution are key challenges for the sustainable development of urban transportation. Researches show that driving behavior accounts a significant proportion many factors affecting traffic ecology. Therefore, reasonable research on safe ecological behaviour can effectively interfere with driver's is conducive to improvement drivers' self-management in awareness, facilitating problems solving. This study uses data constructing predicting general classification system divide...