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Ralph Evins
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Journal Articles
- 2021
- [j1]Paul Westermann
, Theodor Victor Christiaanse
, Will Beckett, Paul Kovacs, Ralph Evins
:
besos: Building and Energy Simulation, Optimization and Surrogate Modelling. J. Open Source Softw. 6(60): 2677 (2021)
Conference and Workshop Papers
- 2021
- [c10]Tianyu Zhang, Gaby M. Baasch, Omid Ardakanian
, Ralph Evins:
On the Joint Control of Multiple Building Systems with Reinforcement Learning. e-Energy 2021: 60-72 - 2019
- [c9]Christoph Waibel
, Ralph Evins, Jan Carmeliet:
Clustering and Ranking Based Methods for Selecting Tuned Search Heuristic Parameters. CEC 2019: 2931-2940 - [c8]Gaby M. Baasch, Adam Wicikowski, Gaëlle Faure, Ralph Evins:
Comparing Gray Box Methods to Derive Building Properties from Smart Thermostat Data. BuildSys@SenSys 2019: 223-232 - [c7]Gaëlle Faure, Theo Christiaanse, Ralph Evins, Gaby M. Baasch:
BESOS: a Collaborative Building and Energy Simulation Platform. BuildSys@SenSys 2019: 350-351 - 2017
- [c6]Ralph Evins, Nigel David:
Using simple predictive models to improve control of complex building systems. BuildSys@SenSys 2017: 26:1-26:4 - 2015
- [c5]L. Andrew Bollinger, Ralph Evins:
Facilitating Model Reuse and Integration in an Urban Energy Simulation Platform. ICCS 2015: 2127-2136 - [c4]Julien F. Marquant, Ralph Evins, Jan Carmeliet:
Reducing Computation Time with a Rolling Horizon Approach Applied to a MILP Formulation of Multiple Urban Energy Hub System. ICCS 2015: 2137-2146 - 2014
- [c3]Ralph Evins, Ravi Vaidyanathan
, Stuart C. Burgess
:
Multi-material Compositional Pattern-Producing Networks for Form Optimisation. EvoApplications 2014: 189-200 - 2010
- [c2]Ralph Evins, Philip Pointer, Ravi Vaidyanathan
:
Configuration of a genetic algorithm for multi-objective optimisation of solar gain to buildings. GECCO 2010: 1327-1328 - [c1]Ralph Evins:
Configuration of a genetic algorithm for multi-objective optimisation of solar gain to buildings. GECCO (Companion) 2010: 2003-2006
Informal and Other Publications
- 2020
- [i1]Paul Westermann, Ralph Evins:
Using Bayesian deep learning approaches for uncertainty-aware building energy surrogate models. CoRR abs/2010.03029 (2020)
Coauthor Index
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