{"product_id":"ai-time-series-control-system-chuzo-ninagawa-9789811945939","title":"AI Time Series Control System Modelling","description":"\u003cp\u003eChapter 1 Introduction\u003c\/p\u003e \u003cp\u003e1.1 Time Series\u003c\/p\u003e \u003cp\u003e1.1.1 What is the \"Time Series\" Dealt with in this Book?\u003c\/p\u003e \u003cp\u003e1.1.2 Time Series for Statistical Control \u003c\/p\u003e \u003cp\u003e1.1.3 Dissemination of Time Series Data for Control \u003c\/p\u003e \u003cp\u003e1.2 Time Series and Control Models \u003c\/p\u003e \u003cp\u003e1.2.1 Control Modeling\u003c\/p\u003e \u003cp\u003e1.2.2 Control Model Building Methods\u003c\/p\u003e \u003cp\u003e1.3 Control Time Series and AI Methods\u003c\/p\u003e \u003cp\u003e1.3.1 Control Model by Time Series Analysis\u003c\/p\u003e \u003cp\u003e1.3.2 Control and AI Methods\u003c\/p\u003e \u003cp\u003eChapter 2 Linear Time Series Modeling\u003c\/p\u003e \u003cp\u003e2.1 Linear Regression Models\u003c\/p\u003e \u003cp\u003e2.1.1 Regression Model\u003c\/p\u003e \u003cp\u003e2.1.2 Multiple Regression Model and its Parameter Estimation\u003c\/p\u003e 2.2 Fundamentals of AR Models\u003cp\u003e\u003c\/p\u003e \u003cp\u003e2.2.1 Overview of the AR model\u003c\/p\u003e \u003cp\u003e2.2.2 Yule-Walker Method (One Variable)\u003c\/p\u003e \u003cp\u003e2.2.3 Yule-Walker Method (Multivariate)\u003c\/p\u003e 2.3 Practical Example 1: Multiple Regression Model with Stable Interval\u003cp\u003e\u003c\/p\u003e \u003cp\u003e2.3.1 Air-conditioning stable power model\u003c\/p\u003e \u003cp\u003e2.3.2 Selection of explanatory variables\u003c\/p\u003e \u003cp\u003e2.3.3 Linear Multiple Regression Analysis\u003c\/p\u003e \u003cp\u003e2.3.4 Model Evaluation and Validation\u003c\/p\u003e \u003cp\u003e2.4 Practical Example 2: Step Response AR Model\u003c\/p\u003e \u003cp\u003e2.4.1 Limit Control of Building Air-conditioning Power\u003c\/p\u003e \u003cp\u003e2.4.2 Fitting the AR Equation Model\u003c\/p\u003e \u003cp\u003e2.4.3 Model Identification from Measured Data\u003c\/p\u003e \u003cp\u003e2.4.4 AR Model Identification Results\u003c\/p\u003e \u003cp\u003eChapter 3 Deep Learning AI Modeling\u003c\/p\u003e 3.1 Fundamentals of Deep Learning\u003cp\u003e\u003c\/p\u003e \u003cp\u003e3.1.1 Fundamentals of Neural Networks\u003c\/p\u003e \u003cp\u003e3.1.2 Principles of Deep Learning\u003c\/p\u003e \u003cp\u003e3.1.3 Stacked Denoising Autoencoder Method\u003c\/p\u003e \u003cp\u003e3.2 Time Series Data Deep Learning\u003c\/p\u003e \u003cp\u003e3.2.1 Time Series Parallel Input Neural Network \u003c\/p\u003e \u003cp\u003e3.2.2 Number of Layers for Time Series Deep Learning \u003c\/p\u003e \u003cp\u003e3.2.3 Hyper parameters of Time Series Deep Learning\u003c\/p\u003e \u003cp\u003e3.3 Practical Example 3: Step Response AR Neural Network \u003c\/p\u003e \u003cp\u003e3.3.1 Step Response AR Neural Network\u003c\/p\u003e \u003cp\u003e3.3.2 Training a Step Response Time Series Model\u003c\/p\u003e 3.3.3 Evaluating the Step Response Time Series Model\u003cp\u003e\u003c\/p\u003e \u003cp\u003e3.4 Example 4: Deep Learning in Practice - Sudden Event Prediction Model\u003c\/p\u003e \u003cp\u003e3.4.1 Example of a Sudden Event \u003c\/p\u003e \u003cp\u003e3.4.2 Sudden Event Prediction Neural Network Model\u003c\/p\u003e \u003cp\u003e3.4.3 Training a Sudden Event Prediction Neural Network Model\u003c\/p\u003e \u003cp\u003eChapter 4 LSTM AI Modeling \u003c\/p\u003e \u003cp\u003e4.1 Fundamentals of LSTM Neural Networks\u003c\/p\u003e 4.1.1 What is LSTM Neural Network?\u003cp\u003e\u003c\/p\u003e \u003cp\u003e4.1.2 LSTM Forward Propagation Calculation\u003c\/p\u003e \u003cp\u003e4.1.3 LSTM Back Propagation Calculation\u003c\/p\u003e \u003cp\u003e4.2 LSTM Time Series Models\u003c\/p\u003e \u003cp\u003e4.2.1 Construction of LSTM Time Series Model\u003c\/p\u003e \u003cp\u003e4.2.2 Predictive Performance Evaluation Method\u003c\/p\u003e \u003cp\u003e4.2.3 Results of Predictive Performance Evaluation\u003c\/p\u003e \u003cp\u003e4.2.4 Considerations for Applying the LSTM Predictive Model\u003c\/p\u003e \u003cp\u003e4.3 Example 5: Electricity Wholesale Market LSTM Model\u003c\/p\u003e \u003cp\u003e4.3.1 Prediction of Wholesale Electricity Prices \u003c\/p\u003e \u003cp\u003e4.3.2 Electricity Wholesale Price LSTM Forecasting Model \u003c\/p\u003e 4.3.3 Evaluation of the Wholesale Electricity Price LSTM Forecasting Model\u003cp\u003e\u003c\/p\u003e \u003cp\u003e4.4 Example 6: LSTM Model for Prediction of Equipment Occurrence Events\u003c\/p\u003e \u003cp\u003e4.4.1 Example of a Time-Series Unexpected Event\u003c\/p\u003e \u003cp\u003e4.4.2 Complexity of Equipment Maintenance Operation\u003c\/p\u003e \u003cp\u003e4.4.3 Prediction Model for Equipment Maintenance Operation\u003c\/p\u003e \u003cp\u003e4.4.4 Evaluation of Predictive Model for Equipment Maintenance Operation\u003c\/p\u003e \u003cp\u003eChapter 5 Optimal Control by Time-Series AI Model\u003c\/p\u003e 5.1 Fundamentals of Optimal Search Control\u003cp\u003e\u003c\/p\u003e \u003cp\u003e5.1.1 Simulated Annealing Optimal Search Method\u003c\/p\u003e \u003cp\u003e5.1.2 Principle of SA Optimal Search Algorithm\u003c\/p\u003e \u003cp\u003e5.1.3 Example of Evaluation Function of SA Optimal Search Control\u003c\/p\u003e \u003cp\u003e5.2 State Explosion and Parallel Search\u003c\/p\u003e \u003cp\u003e5.2.1 Large-scale State Space to be Controlled\u003c\/p\u003e \u003cp\u003e5.2.2 Parallel SA Search Algorithm\u003c\/p\u003e \u003cp\u003e5.2.3 Trials of Large-scale Parallel Search\u003c\/p\u003e \u003cp\u003e5.3 Example 7: Electric\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Chuzo Ninagawa\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 9811945934\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9789811945939\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Springer\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 09\/03\/2022\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 237\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Hardcover\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.17lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.21h x 6.14w x 0.63d\u003c\/p\u003e","brand":"Chuzo Ninagawa","offers":[{"title":"Hardcover","offer_id":44829522821375,"sku":"9789811945939","price":109.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_e8b50918-99e5-4363-bca1-3925a1b26528.jpg?v=1708451030","url":"https:\/\/www.whiterainbookhouse.com\/products\/ai-time-series-control-system-chuzo-ninagawa-9789811945939","provider":"WR Book House","version":"1.0","type":"link"}