Journal ArticleDOI
A review on time series forecasting techniques for building energy consumption
TLDR
The various combinations of the hybrid model are found to be the most effective in time series energy forecasting for building and the nine most popular forecasting techniques based on the machine learning platform are analyzed.Abstract:
Energy consumption forecasting for buildings has immense value in energy efficiency and sustainability research. Accurate energy forecasting models have numerous implications in planning and energy optimization of buildings and campuses. For new buildings, where past recorded data is unavailable, computer simulation methods are used for energy analysis and forecasting future scenarios. However, for existing buildings with historically recorded time series energy data, statistical and machine learning techniques have proved to be more accurate and quick. This study presents a comprehensive review of the existing machine learning techniques for forecasting time series energy consumption. Although the emphasis is given to a single time series data analysis, the review is not just limited to it since energy data is often co-analyzed with other time series variables like outdoor weather and indoor environmental conditions. The nine most popular forecasting techniques that are based on the machine learning platform are analyzed. An in-depth review and analysis of the ‘hybrid model’, that combines two or more forecasting techniques is also presented. The various combinations of the hybrid model are found to be the most effective in time series energy forecasting for building.read more
Citations
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Journal ArticleDOI
A time series forecasting analysis of overall and sector-based natural gas demand: a developing South Asian economy case
Predicción del consumo de energía eléctrica residencial de la Región Cajamarca mediante modelos Holt -Winters/Prediction of residential electric power consumption in the Cajamarca Region through Holt -Winters models
TL;DR: In this paper, the authors predict the consumption of residential electrical energy in the Cajamarca Region through Holt-Winters models for different smoothing constants, which includes methods for seasonal additive and multiplicative patterns.
Journal ArticleDOI
An Empirical Comparison of the Sales Forecasting Performance for Plastic Tray Manufacturing Using Missing Data
TL;DR: In this paper , a dedicated time series forecasting scheme is presented, which is both accurate and sustainable, and a practical observation of the data background to deal with the problem of missing data and to effectively formulate correction strategies after predictions.
Journal ArticleDOI
Prognosticating the effect on Unemployment rate in the post-pandemic India via Time-Series Forecasting and Least Squares Approximation
TL;DR: This study proposes a novel architecture to deal with these rare unusual trends by combining two models - one learning normal usual patterns and the other getting trained on usual as well as rare anomalous patterns.
Journal ArticleDOI
Studying Thermal and Mechanical Properties of Recycled Concrete by Using Ceramic Aggregate
TL;DR: In this article , the impact of replacing natural coarse aggregate with ceramic aggregate and natural sand with recycled fine aggregate, on the physical, mechanical, and thermal properties of concrete was studied, and a total of five concrete mixes were prepared with different levels of ceramic aggregate (0, 30, 50, 70, 100%).
References
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Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Journal ArticleDOI
Learning representations by back-propagating errors
TL;DR: Back-propagation repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector, which helps to represent important features of the task domain.
Journal ArticleDOI
A logical calculus of the ideas immanent in nervous activity
Warren S. McCulloch,Walter Pitts +1 more
TL;DR: In this article, it is shown that many particular choices among possible neurophysiological assumptions are equivalent, in the sense that for every net behaving under one assumption, there exists another net which behaves under another and gives the same results, although perhaps not in the same time.
Journal ArticleDOI
The perceptron: a probabilistic model for information storage and organization in the brain.
TL;DR: This article will be concerned primarily with the second and third questions, which are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory.
Book
The perception: a probabilistic model for information storage and organization in the brain
TL;DR: The second and third questions are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory as mentioned in this paper.
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