Search
Now showing items 31-37 of 37
Feature extraction for enhancing data-driven urban building energy models
(European Council on Computing in Construction (EC3), 2023)
Building energy demand assessment plays a crucial role in designing energy-efficient building stocks. However, most studies adopting a data-driven approach feel the deficiency of datasets with building-specific information ...
A new era of modeling MOF-based membranes: Cooperation of theory and data science
(Wiley, 2024-01)
Membrane-based separation can offer significant energy savings over conventional separation methods. Given their highly customizable and porous structures, metal–organic frameworks- (MOFs) are considered as next-generation ...
Big data–enabled sign prediction for Borsa Istanbul intraday equity prices
(Elsevier, 2023-12)
This paper employs a big data source, the Borsa Istanbul's “data analytics” information, to predict 5-min up, down, and steady signs drawn from closing price changes. Seven machine learning algorithms are compared with ...
Simulation of vehicles’ gap acceptance decision at unsignalized intersections using SUMO
(Elsevier, 2022)
In this paper, an artificial neural network (ANN)-based gap acceptance behavior model was proposed. The feasibility of implementing this model in a microscopic simulation tool was tested using the application programming ...
Incremental analysis of large-scale system logs for anomaly detection
(IEEE, 2019)
Anomalies during system execution can be detected by automated analysis of logs generated by the system. However, large scale systems can generate tens of millions of lines of logs within days. Centralized implementations ...
Evaluation of distributed machine learning algorithms for anomaly detection from large-scale system logs: a case study
(IEEE, 2018)
Anomaly detection is a valuable feature for detecting and diagnosing faults in large-scale, distributed systems. These systems usually provide tens of millions of lines of logs that can be exploited for this purpose. ...
Evaluation of linguistic and prosodic features for detection of Alzheimer’s disease in Turkish conversational speech
(Springer Science+Business Media, 2015-12)
Automatic diagnosis and monitoring of Alzheimer’s disease can have a significant impact on society as well as the well-being of patients. The part of the brain cortex that processes language abilities is one of the earliest ...
Share this page