Soowon Chang
Datos Biográficos
| ID | 6904591 |
|---|---|
| NOMBRE | Soowon Chang |
| NOMBRES | Soowon |
| APELLIDO | Chang |
| FIRMA | CHANG S |
| AFILIACIONES | Purdue University West Lafayette |
| ORCID | 0000-0003-4877-2934 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 5 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 5 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2020 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2026 |
| ÍNDICE H | 0 |
Strategic and Equitable Allocation of Electric Vehicle Fast Charging Stations using Geospatial-Aware Multi-Objective Deep Reinforcement Learning
Integrating social justice criteria into multiscale spatial modeling of energy burden
Optimal planning for electric vehicle fast charging stations placements in a city scale using an advantage actor-critic deep reinforcement learning and geospatial analysis
Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities
To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized e…
Data-driven planning support system for a campus design
The paper aims to develop a campus-level planning support system that is driven by data analytics by comparing two design approaches, anticipation and optimization. A campus is defined as a small-scale complex urban system of buildings and infrastructure. Three questions are addressed: (1) What generates campus design? What principles are taken for making design decisions? (2) How do we optimize design options based on multi-criteria performance …
Sin obras prominentes en esta página.
Data-driven planning support system for a campus design
The paper aims to develop a campus-level planning support system that is driven by data analytics by comparing two design approaches, anticipation and optimization. A campus is defined as a small-scale complex urban system of buildings and infrastructure. Three questions are addressed: (1) What generates campus design? What principles are taken for making design decisions? (2) How do we optimize design options based on multi-criteria performance …
Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities
To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized e…
Optimal planning for electric vehicle fast charging stations placements in a city scale using an advantage actor-critic deep reinforcement learning and geospatial analysis
Strategic and Equitable Allocation of Electric Vehicle Fast Charging Stations using Geospatial-Aware Multi-Objective Deep Reinforcement Learning
Integrating social justice criteria into multiscale spatial modeling of energy burden
Engineering (3 obras) · Cartography (2 obras) · Computer Science (2 obras) · Electric Vehicles and Infrastructure (2 obras) · Geography (2 obras) · Reinforcement learning (2 obras) · Transportation and Mobility Innovations (2 obras) · Advanced battery technologies research (1 obras) · Algal biology and biofuel production (1 obras) · Analytics (1 obras)