Hybrid advanced techniques forecasting (40 résultats)

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Paperback or Softback. Etat : New. Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting. Book.

Paperback or Softback. Etat : New. Hybrid Advanced Techniques for Forecasting in Energy Sector. Book.

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Paperback. Etat : New. Illustrated.

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Etat : New. In English.

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Taschenbuch. Etat : Neu. Neuware - Reactive PublishingIn today's volatile business landscape, forecasting isn't just about predicting numbers, it's about engineering foresight. In Forecasting with Precision, Graham Wexler unveils a cutting-edge framework that blends financial modeling, scenario planning, and analytical discipline into a unified forecasting methodology used by top-performing FP&A teams worldwide.Through practical models, case-based examples, and advanced techniques, Wexler shows how to transform uncertainty into strategic advantage, bridging the gap between traditional spreadsheet forecasting and modern data-driven finance. You'll learn to build driver-based models, master multi-scenario sensitivity analysis, and deploy real-time predictive models using Python, Power BI, and advanced analytics platforms.From constructing resilient forecasting architectures to communicating actionable insights to executives, this book is a complete roadmap for FP&A professionals, analysts, and CFOs who want to elevate their craft and lead with precision in a data-saturated world.Key insights include: - Designing scalable, dynamic financial models for evolving business realities- Applying Monte Carlo simulations and probabilistic forecasting methods- Integrating macroeconomic and operational data for holistic visibility- Building adaptive scenario frameworks to support strategic agility- Turning financial data into a predictive narrative that drives enterprise actionForecasting with Precision sets a new standard for modern FP&A mastery, combining technical depth, strategic clarity, and the real-world foresight required to thrive in global finance.…

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

Kartoniert / Broschiert. Etat : New. KlappentextrnrnAccurate forecasting performance in the energy sector is a primary factor in the modern restructured power market, accomplished by any novel advanced hybrid techniques. Particularly in the Big Data era, forecasting models are alwa.

Etat : New. KlappentextrnrnMore accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, a.

Taschenbuch. Etat : Neu. Neuware - Accurate forecasting performance in the energy sector is a primary factor in the modern restructured power market, accomplished by any novel advanced hybrid techniques. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated by factors such as seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. To comprehensively address this issue, it is insufficient to concentrate only on simply hybridizing evolutionary algorithms with each other, or on hybridizing evolutionary algorithms with chaotic mapping, quantum computing, recurrent and seasonal mechanisms, and fuzzy inference theory in order to determine suitable parameters for an existing model. It is necessary to also consider hybridizing or combining two or more existing models (e.g., neuro-fuzzy model, BPNN-fuzzy model, seasonal support vector regression-chaotic quantum particle swarm optimization (SSVR-CQPSO), etc.). These advanced novel hybrid techniques can provide more satisfactory energy forecasting performances.This book aimed to attract researchers with an interest in the research areas described above. Specifically, we were interested in contributions towards recent developments, i.e., hybridizing or combining any advanced techniques in energy forecasting, with the superior capabilities over the traditional forecasting approaches, with the ability to overcome some embedded drawbacks, and with the very superiority to achieve significant improved forecasting accuracy.…

Taschenbuch. Etat : Neu. Neuware - More accurate and precise energy demand forecasts are required when energy decisions are made in a competitive environment. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated. Examples include seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. These forecasting models have resulted in an over-reliance on the use of informal judgment and higher expenses when lacking the ability to determine data characteristics and patterns. The hybridization of optimization methods and superior evolutionary algorithms can provide important improvements via good parameter determinations in the optimization process, which is of great assistance to actions taken by energy decision-makers.This book aimed to attract researchers with an interest in the research areas described above. Specifically, it sought contributions to the development of any hybrid optimization methods (e.g., quadratic programming techniques, chaotic mapping, fuzzy inference theory, quantum computing, etc.) with advanced algorithms (e.g., genetic algorithms, ant colony optimization, particle swarm optimization algorithm, etc.) that have superior capabilities over the traditional optimization approaches to overcome some embedded drawbacks, and the application of these advanced hybrid approaches to significantly improve forecasting accuracy.…

Paperback. Etat : New. Illustrated.

Paperback. Etat : New. Illustrated.

paperback. Etat : New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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