The Fuzzy Logic Toolbox™ product extends the MATLAB® technical computing environment with tools for designing systems based on fuzzy logic. Graphical user interfaces (GUIs) guide you through the steps of fuzzy inference system design. Functions are provided for many common fuzzy logic methods, including fuzzy clusterINg and adaptive neurofuzzy learning.
Quartz is a full-featured, open source job scheduling system that can be integrated with, or used along side virtually any J2EE or J2SE application - from the smallest stand-alone application to the largest e-commerce system. Quartz can be used to create simple or complex schedules for executing tens, hundreds, or even tens-of-thousands of jobs jobs whose tasks are defined as standard Java components or EJBs. The Quartz Scheduler includes many enterprise-class features, such as JTA transactions and clusterINg.
Quartz is freely usable, licensed under the Apache 2.0 license.
Smart Grids provide many benefits for society. Reliability, observability across the
energy distribution system and the exchange of information between devices are just
some of the features that make Smart Grids so attractive. One of the main products of
a Smart Grid is to data. The amount of data available nowadays increases fast and carries
several kinds of information. Smart metres allow engineers to perform multiple
measurements and analyse such data. For example, information about consumption,
power quality and digital protection, among others, can be extracted. However, the main
challenge in extracting information from data arises from the data quality. In fact, many
sectors of the society can benefit from such data. Hence, this information needs to be
properly stored and readily available. In this chapter, we will address the main concepts
involving Technology Information, Data Mining, Big Data and clusterINg for deploying
information on Smart Grids.
Smart Grids provide many benefits for society. Reliability, observability across the
energy distribution system and the exchange of information between devices are just
some of the features that make Smart Grids so attractive. One of the main products of
a Smart Grid is to data. The amount of data available nowadays increases fast and carries
several kinds of information. Smart metres allow engineers to perform multiple
measurements and analyse such data. For example, information about consumption,
power quality and digital protection, among others, can be extracted. However, the main
challenge in extracting information from data arises from the data quality. In fact, many
sectors of the society can benefit from such data. Hence, this information needs to be
properly stored and readily available. In this chapter, we will address the main concepts
involving Technology Information, Data Mining, Big Data and clusterINg for deploying
information on Smart Grids.
壓縮包中有5篇論文，分別為《Data-driven analysis of variables and dependencies in continuous optimization problems and EDAs》這是一篇博士論文，較為詳細的介紹了各種EDA算法；《Anisotropic adaptive variance scaling for Gaussian estimation of distribution algorithm》《Enhancing Gaussian Estimation of Distribution Algorithm by Exploiting Evolution Direction with Archive》《Niching an Archive-based Gaussian Estimation of Distribution Algorithm via Adaptive clusterINg》《Supplementary material for Enhancing Gaussian Estimation of Distribution Algorithm by Exploiting Evolution Direction with Archive》《基于一般二階混合矩的高斯分布估計算法》介紹了一些基于EDA的創新算法。
