Browsing UTSA Faculty and Staff Works by Author "Alamaniotis, Miltiadis"
Now showing items 1-6 of 6
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An Intelligent Approach for Performing Energy-Driven Classification of Buildings Utilizing Joint Electricity–Gas Patterns
Nichiforov, Cristina; Martinez-Molina, Antonio; Alamaniotis, Miltiadis (11/9/2021)Building type identification is an important task that may be used in confirming and verifying its legitimate operation. One of the main sources of information over the operation of a building is its energy consumption, ... -
Enhancing Historic Building Performance with the Use of Fuzzy Inference System to Control the Electric Cooling System
Martinez-Molina, Antonio; Alamaniotis, Miltiadis (Sustainability;Volume 12, Issue 14, 7/21/2020)In recent years, the interest in properly conditioning the indoor environment of historic buildings has increased significantly. However, maintaining a suitable environment for building and artwork preservation while keeping ... -
Evolutionary Multi-Objective Cost and Privacy Driven Load Morphing in Smart Electricity Grid Partition
Alamaniotis, Miltiadis; Gatsis, Nikolaos (6/26/2019)Utilization of digital connectivity tools is the driving force behind the transformation of the power distribution system into a smart grid. This paper places itself in the smart grid domain where consumers exploit digital ... -
Improving Road Safety during Nocturnal Hours by Characterizing Animal Poses Utilizing CNN-Based Analysis of Thermal Images
Mowen, Derian; Munian, Yuvaraj; Alamaniotis, Miltiadis (2022-09-25)Animal–vehicle collision is a common danger on highways, especially during nighttime driving. Its likelihood is affected not only by the low visibility during nighttime hours, but also by the unpredictability of animals' ... -
Intelligent Room-Based Identification of Electricity Consumption with an Ensemble Learning Method in Smart Energy
Le, Vincent; Ramirez, Joshua; Alamaniotis, Miltiadis (10/15/2021)This paper frames itself in the realm of smart energy technologies that can be utilized to satisfy the electricity demand of consumers. In this environment, demand response programs and the intelligent management of energy ... -
Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques
Arvanitidis, Athanasios Ioannis; Bargiotas, Dimitrios; Kontogiannis, Dimitrios; Fevgas, Athanasios; Alamaniotis, Miltiadis (2022-10-25)In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. ...