Towards optimal control of air handling units using deep reinforcement learning and recurrent neural network
Optimal control of heating, ventilation and air conditioning systems (HVACs) aims to
minimize the energy consumption of equipment while maintaining the thermal comfort of …
minimize the energy consumption of equipment while maintaining the thermal comfort of …
A data-driven approach to extract operational signatures of HVAC systems and analyze impact on electricity consumption
The electricity consumption of Heating Ventilating and Air Conditioning (HVAC) systems has
a significant share in the energy consumption of buildings, which account for 75% of total …
a significant share in the energy consumption of buildings, which account for 75% of total …
How far back shall we peer? Optimal air handling unit control leveraging extensive past observations
Abstract Heating, Ventilation, and Air Conditioning (HVAC) systems play a critical role in
ensuring occupant comfort in buildings. Traditional Rule-Based Feedback Control (RBFC) …
ensuring occupant comfort in buildings. Traditional Rule-Based Feedback Control (RBFC) …
Enhanced directed random walk for the identification of breast cancer prognostic markers from multiclass expression data
Artificial intelligence in healthcare can potentially identify the probability of contracting a
particular disease more accurately. There are five common molecular subtypes of breast …
particular disease more accurately. There are five common molecular subtypes of breast …
Integrated optimization of energy systems in buildings: from demand responsive battery storage to intelligent HVAC control
R Li - 2024 - open.library.ubc.ca
This thesis introduces an integrated approach aimed at boosting energy efficiency and
advancing sustainability in buildings via innovative Demand Response (DR) programs and …
advancing sustainability in buildings via innovative Demand Response (DR) programs and …
[PDF][PDF] SEF-USIEF FEATURE SELECTOR: AN APPROACH TO SELECT EFFECTIVE FEATURES AND UNSELECT INEFFECTIVE FEATURES.
S Sivakumar, S Venkataraman… - ICTACT Journal on Soft …, 2023 - ictactjournals.in
Feature selection is a method in Data mining to reduce the features from the original dataset
by removing the noisy features from the dataset to improve the performance of the classifiers …
by removing the noisy features from the dataset to improve the performance of the classifiers …
Computed Tomography Liver Tumor Image Classification Using Hybrid Feature Extraction and Classification Techniques
PVB Reddy, MP Arakeri - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Accurate diagnosis of liver tumor is important task for the physician. The purpose of this
research work is to investigate the utility of feature extraction and classification techniques in …
research work is to investigate the utility of feature extraction and classification techniques in …
[PDF][PDF] Identification of pathway and gene markers using enhanced directed random walk for multiclass cancer expression data
NHUI WEN - 2020 - eprints.utm.my
Cancer markers play a significant role in the diagnosis of the origin of cancers and in the
detection of cancers from initial treatments. This is a challenging task owing to the …
detection of cancers from initial treatments. This is a challenging task owing to the …