£54.23

Springer Fractional-Order Activation Functions for Neural Networks

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Description

Explore advanced computational methods in this specialized academic volume from Springer. Part of the Studies in Systems, Decision and Control series (Volume 588), this book focuses on fractional-order activation functions for neural networks. It provides specific case studies regarding the forecasting of wind turbines' generated power, making it a valuable resource for researchers and professionals in the field of AI and machine learning. This publication addresses complex problems in system decision-making and control. By examining the application of fractional-order mathematics within neural network frameworks, the text offers technical insights into improving power forecasting accuracy. It is an essential addition to any library focused on computer science, artificial intelligence, and renewable energy forecasting technologies.

Key Features

Part of the Springer Studies in Systems, Decision and Control series, volume 588.

Focuses on the application of fractional-order activation functions within neural networks.

Provides detailed case studies on forecasting generated power for wind turbines.

Targeted content for specialists in AI, machine learning, and computer science.

Technical research regarding system decision and control methodologies.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
24 May 2025
Listed Since
17 February 2025

Barcode

No barcode data available

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