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  MIC (Maximum Information Coefficient) Information MIC (Maximum Information Coefficient) is a measure of the strength of the linear or nonlinear association between two variables. MIC ranges between 0 and 1, where 0 indicates no association and 1 indicates perfect association. It is a nonparametric method that uses mutual information as a measure of association between two variables. MIC is scale-invariant, which means it can be used.. Zettelkasten/Terminology Information 2023. 4. 20.

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  ReLU (Rectified Linear Unit) Information ReLU (Rectified Linear Unit) is a type of activation function used in neural networks, which is defined as f(x) = max(0,x). It returns 0 for all negative inputs and returns the input as it is for all positive inputs. ReLU is a popular choice for activation function due to its simplicity and effectiveness in reducing vanishing gradients in deep neural networks. Vanishing gradients occ.. Zettelkasten/Terminology Information 2023. 4. 19.

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  MLP (Multi-Layer Perceptron) Information MLP (Multi-Layer Perceptron) is a type of feedforward artificial neural network (ANN) that consists of multiple layers of nodes. It is composed of an input layer, one or more hidden layers, and an output layer. Each node in a layer is connected to every node in the next layer, forming a dense graph. MLP is trained using backpropagation, a supervised learning technique that adjusts th.. Zettelkasten/Terminology Information 2023. 4. 18.

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  RES (Renewable Energy Source) Information RES (Renewable Energy Source) RES (Renewable Energy Source) is source of energy that are replenished naturally and can be replenished over a relatively short period of time. Examples of RES (Renewable Energy Source) include solar, wind, hydro, geothermal, and biomass. RES (Renewable Energy Source) are a growing area of interest due to concerns about climate change and the need to red.. Zettelkasten/Terminology Information 2023. 4. 17.

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  ESS (Energy Storage System) Information An ESS (Energy Storage System) is a technology that stores energy in the form of electrical energy, chemical energy, or thermal energy, for later use. ESS can help to balance the energy supply and demand in the power grid, and integrate renewable energy sources by storing excess energy and releasing it when needed. ESS can also help to provide backup power during outages, reduce peak.. Zettelkasten/Terminology Information 2023. 4. 16.

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  BC Hydro (British Columbia Hydro) dataset Information BC Hydro (British Columbia Hydro) is a Canadian electric utility company, serving customers in the province of British Columbia. The BC Hydro dataset provides hourly electricity demand data for the province of British Columbia. The dataset contains historical hourly electricity demand data for the entire province, as well as for specific regions and communities within the province. T.. Zettelkasten/Terminology Information 2023. 4. 16.

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  EMS (Energy Management System) Information EMS (Energy Management System) is a computer-based system that helps to monitor, control and optimize energy usage and consumption in a building, factory or organization. It helps to improve the efficiency of energy usage by monitoring and controlling the energy consumption of various equipment and systems in real-time. EMS systems use various data collection techniques, including su.. Zettelkasten/Terminology Information 2023. 4. 15.

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  EA (Electricity Authority) dataset Information The New Zealand Electricity Authority (EA) manages the electricity industry in New Zealand. The EA dataset is publicly available and includes data related to electricity demand, prices, and other market-related information. The dataset provides access to historical and real-time data on electricity supply and demand, as well as transmission and distribution constraints. The EA datase.. Zettelkasten/Dataset Information 2023. 4. 15.

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  Univariate forecasting Information Univariate forecasting is a time series forecasting technique that involves analyzing a single variable's past values to predict its future values. It assumes that the variable of interest's past values are the most relevant predictor of its future values. Univariate models do not consider the relationship between the variable of interest and other related variables. The most common .. Zettelkasten/Terminology Information 2023. 4. 14.

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  ESB (Electricity Supply Board) dataset Information The dataset consists of smart meter data collected from approximately 5,000 households and small businesses in Ireland between 2009 and 2013. The data includes half-hourly readings of electricity consumption, as well as some additional data such as weather data, holidays, and other events that may affect electricity consumption. The dataset is anonymized to protect the privacy of the.. Zettelkasten/Dataset Information 2023. 4. 14.

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  Multivariate forecasting Information Multivariate forecasting is a type of time series forecasting that involves predicting multiple variables simultaneously. This approach uses the relationships and dependencies between the variables to make accurate predictions. Multivariate forecasting can be useful in situations where the variables are interdependent and affect each other, making it difficult to predict one variable.. Zettelkasten/Terminology Information 2023. 4. 13.

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  CEA (Canadian Electricity Association) dataset Information The dataset is maintained and updated by the Canadian Electricity Association, which represents electric utilities in Canada and is the voice of the Canadian electricity industry. The dataset includes information on electricity generation, transmission, and distribution in Canada, as well as electricity prices and consumption patterns. The data is collected from various sources, incl.. Zettelkasten/Dataset Information 2023. 4. 13.

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  NYSERDA (New York State Energy Research and Development Authority) dataset Information The NYSERDA (New York State Energy Research and Development Authority) is a public benefit corporation that aims to advance innovative energy solutions, technologies, and policies. NYSERDA collects and maintains a variety of datasets related to energy use and production in New York State, including energy consumption data from commercial, industrial, and residential buildings, renewa.. Zettelkasten/Dataset Information 2023. 4. 12.

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  Fourier analysis Information Fourier analysis is a mathematical technique used to represent a time series as a sum of sine and cosine functions with different frequencies. This technique allows us to decompose a complex signal into simpler components that can be easily analyzed and modeled. In time series forecasting, Fourier analysis is used to identify seasonal patterns or cycles in the data. The output of Fou.. Zettelkasten/Terminology Information 2023. 4. 12.

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  STL (Seasonal-Trend decomposition using LOESS) Information The STL (Seasonal-Trend decomposition using LOESS) is a method used to decompose time series data into three main components: trend, seasonal, and residual. The trend component represents the long-term pattern or behavior in the time series. The seasonal component represents the repeating pattern that occurs within the time series over a fixed period of time, such as weekly or monthl.. Zettelkasten/Terminology Information 2023. 4. 11.

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  JEPX (Japan Electric Power Exchange) dataset Information JEPX (Japan Electric Power Exchange) is a dataset that provides information on the electricity supply and demand in Japan JEPX is operated by the Japan Electric Power Exchange Corporation, which was established in 2003 as an independent entity to promote fair competition and transparency in the Japanese electricity market. JEPX provides data on the hourly supply and demand of electri.. Zettelkasten/Dataset Information 2023. 4. 11.

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  CNE (Comisión Nacional de Energía) dataset Information The CNE (Comisión Nacional de Energía) dataset provides comprehensive data on energy supply, demand, and prices in Chile. The dataset includes detailed information on electricity generation, transmission, and distribution, as well as energy consumption by sector and energy source. The CNE dataset also provides data on electricity prices, including spot prices and regulated prices, as.. Zettelkasten/Dataset Information 2023. 4. 10.

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  Time series forecasting Information Time series forecasting is a technique used to make predictions about future values based on past observations of a time series dataset. A time series is a sequence of data points recorded over time, typically at regular intervals. The goal of time series forecasting is to identify patterns and trends in the time series data and use them to predict future values. Time series forecast.. Zettelkasten/Terminology Information 2023. 4. 10.

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  OPSD (Open Power System Data) dataset Information The OPSD (Open Power System Data) dataset provides detailed information on electricity generation and consumption in 30 European countries. The dataset includes hourly and daily data on electricity generation and consumption, allowing for the analysis of trends over time and the study of seasonal variations in electricity demand and generation. In addition to data on fossil fuel gene.. Zettelkasten/Dataset Information 2023. 4. 9.

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  Transformer Information Transformer is a deep learning architecture that was introduced in a 2017 paper by Vaswani et al. for natural language processing tasks. Unlike traditional RNNs, Transformers don't use sequential processing to learn context from a sequence of inputs. Instead, they use a self-attention mechanism to process all input positions simultaneously. The architecture of the Transformer is comp.. Zettelkasten/Terminology Information 2023. 4. 9.