Predicting personal thermal preferences based on data-driven methods
نویسندگان
چکیده
منابع مشابه
predicting streamflow using data-driven model and time series
accurate forecasting of streamflows has been one of the most important issues as it plays a key role in allotment of water resources. river flow simulations to determine the future river flows are important and practical. given the importance of flow in the coming years, in this research three stations: haji qooshan, ghare shoor and tamar in gorganrood cachment were simulated in 2002-2011. to s...
متن کاملPredicting coping self-efficacy based on social support, personal growth, and mindfulness in people with cancer
One of the most significant and complex health issues in our country is cancer. Coping with psychological syptoms of cancer such as stress, anxiety and depression is the most challenging blind spot for patients suffering from the cancer. The purpose of this study is to predict coping self-efficacy based on social support, personal growth and mindfulness in people with cancer. 120 participants w...
متن کاملEEG/fMRI fusion based on independent component analysis: integration of data-driven and model-driven methods.
Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary noninvasive information of brain activity, and EEG/fMRI fusion can achieve higher spatiotemporal resolution than each modality separately. This focuses on independent component analysis (ICA)-based EEG/fMRI fusion. In order to appreciate the issues, we first describe the potential an...
متن کاملPredicting User Preferences Via Similarity-Based Clustering
This paper explores the idea of clustering partial preference relations as a means for agent prediction of users’ preferences. Due to the high number of possible outcomes in a typical scenario, such as an automated negotiation session, elicitation techniques can provide only a sparse specification of a user’s preferences. By clustering similar users together, we exploit the notion that people w...
متن کاملA novel method for detecting structural damage based on data-driven and similarity-based techniques under environmental and operational changes
The applications of time series modeling and statistical similarity methods to structural health monitoring (SHM) provide promising and capable approaches to structural damage detection. The main aim of this article is to propose an efficient univariate similarity method named as Kullback similarity (KS) for identifying the location of damage and estimating the level of damage severity. An impr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: E3S Web of Conferences
سال: 2019
ISSN: 2267-1242
DOI: 10.1051/e3sconf/201911105015