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another debate! However, the contents of this book may help to shed some light on the answer to this question A more recent de nition of arti cial intelligence came from the IEEE Neural Networks Council of 1996: the study of how to make computers do things at which people are doing better A de nition that is awed, but this is left to the reader to explore in one of the assignments at the end of this chapter This book concentrates on a sub-branch of AI, namely Computational Intelligence (CI) the study of adaptive mechanisms to enable or facilitate intelligent behavior in complex and changing environments These mechanisms include those AI paradigms that exhibit an ability to learn or adapt to new situations, to generalize, abstract, discover and associate The following CI paradigms are covered: arti cial neural networks, evolutionary computation, swarm intelligence, arti cial immune systems, and fuzzy systems While individual techniques from these CI paradigms have been applied successfully to solve real-world problems, the current trend is to develop hybrids of paradigms, since no one paradigm is superior to the others in all situations In doing so, we capitalize on the respective strengths of the components of the hybrid CI system, and eliminate weaknesses of individual components The rest of this chapter is organized as follows: Section 11 of this chapter presents a short overview of the di erent CI paradigms, also discussing the biological motivation for each paradigm A short history of AI is presented in Section 12 At this point it is necessary to state that there are di erent de nitions of what constitutes CI This book re ects the opinion of the author, and may well cause some debate For example, swarm intelligence (SI) and arti cial immune systems (AIS) are classi ed as CI paradigms, while many researchers consider these paradigms to belong only under Arti cial Life However, both particle swarm optimization (PSO) and ant colony optimization (ACO), as treated under SI, satisfy the de nition of CI given above, and are therefore included in this book as being CI techniques The same applies to AISs. ssrs ean 13 UPC EAN Barcodes in SQL Server Reporting Services ( SSRS )
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.net barcode reader component Order the SSRS Barcode Generator Service Download the SSRS Barcode Generator Service View the release log for the SSRS Native Generator Forum ... Choose Insert Layer to add a new layer Rename it coverup Choose the Rectangle tool Change the Fill Color to match the background of your movie Change the Stroke Color to No Color Draw a shape that covers up the entire image If necessary, use the Free Transform tool to modify the rectangle s shape or rotation so that the image is completely covered Computational Intelligence: An Introduction, Second Edition AP Engelbrecht c 2007 John Wiley & Sons, Ltd Figure 31 illustrates a standard feedforward neural network (FFNN), consisting of three layers: an input layer (note that some literature on NNs do not count the input layer as a layer), a hidden layer and an output layer While this gure illustrates only one hidden layer, a FFNN can have more than one hidden layer However, it has been proved that FFNNs with monotonically increasing di erentiable functions can approximate any continuous function with one hidden layer, provided that the hidden layer has enough hidden neurons [383] A FFNN can also have direct (linear) connections between the input layer and the output layer ssrs ean 13 EAN - 13 in SSRS
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