Zhipeng ma (12 risultati)
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Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 116,67
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 160,22
EUR 3,42 spedizioneSpedito in U.S.A.Quantità: 4 disponibili
Condizione: New.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 152,72
EUR 11,67 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Paperback. Condizione: Brand New. 407 pages. 5.83x0.91x8.27 inches. In Stock.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 62,63 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential to achieving cl…imate resilience and meeting decarbonization goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analyticalsupport. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact.This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies.
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 116,66
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential to achieving climate resilience and meeting decarbonization… goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analytical support. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact.This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential… to achieving climate resilience and meeting decarbonization goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analyticalsupport. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact.This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies. 366 pp. Englisch.
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 92,27
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 124,97
EUR 43,17 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential to achieving climate resilience and meeting decarbonization… goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analytical support. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact.This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential to…achieving climate resilience and meeting decarbonization goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analyticalsupport. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact. This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies.Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Straße 46, 65189 Wiesbaden 408 pp. Englisch.
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 165,78
EUR 7,58 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.
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- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 170,92
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.
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- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 156,80
EUR 31,75 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Energy-intensive sectors such as industry and transportation are vital to economic development, yet remain major contributors to global energy consumption and greenhouse gas emissions. Enhancing their energy efficiency is essential to achieving climate resilience and meeting decarbonization… goals. Despite abundant operational and sensor data, decision-making in these sectors often relies on heuristics and lacks systematic, transparent, and explainable analytical support. Existing Artificial Intelligence (AI)-based decision support methods frequently fall short in integrating robust data preprocessing, causal interpretation, and actionable recommendation generation, limiting their practical impact.This book develops and validates an AI-driven decision support framework to improve energy efficiency in energy-intensive industrial and transportation systems. Guided by a three-cycle Design Science Research (DSR) methodology, the framework integrates complementary AI techniques into a modular, end-to-end architecture that transforms heterogeneous raw data into interpretable, actionable recommendations. It includes systematic data quality assessment and preprocessing pipelines, time-series segmentation, clustering key performance indicators for pattern recognition, causal inference methods to identify drivers of inefficiency, and a multimodal large language model (LLM)-based decision support module that translates analytical outcomes into domain-relevant strategies. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
