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If such feedback were available, it might be possible to gain better insight into the types of inputs that could enhance the network effectiveness Several techniques have been developed that attempt to provide an interpretation of the connection weights In one method, the partition is used to make judgments about the relative importance of the various inputs The method consists of applying an equation that effectively partitions the middle-to-output layer weights of each middle (hidden-layer) node into components associated with each input node It has been suggested that this method can make ANNs as effective for modeling applications as for pattern matching A more manually intensive method has been proposed for interpreting the weights that entails iteratively presenting speci c isolated features to the trained network and assessing the network s reaction For example, after training the network to recognize seven letters of the alphabet, various features of the letters (such as the angular top of the letter A) were presented to the network, and the responses of each node were examined Through this method, the discriminating features were identi ed In both the above-mentioned methods, it was unclear to what degree the technique s applicability would extend to networks with different architectures and levels of complexity One of the most interesting methods of a weight-interpreting technique was the Knowledgetron (KT) The KT method uses a sophisticated algorithm to walk through the nodes of the network, interpret the connections, and generate a set of if then rules to match the behavior of the network These rules can then become the basis for a rule-based expert system It is particularly noteworthy that the KT technique was able to process the classic Iris data set successfully A set of only ve relatively simple rules were generated from ANN trained on the Iris data In fact, it was found that the generated rules actually outperformed the ANN from which they were generated Because the Iris data set is not particularly complex, it would be premature to assume that the KT technique would scale o more complex, real-world data sets; however, its performance provides evidence that further research in this area would be worthwhile From the perspective of the data issue, the production of rules provides a convenient mechanism for evaluating the importance and role of each input data element This could form the basis for a feedback-and-re ne iterative process to guide the selection and preprocessing of training data, which might result in improved ANN performance From the foregoing discussion, it can be observed that the range of techniques and possibilities for enhancing ANN effectiveness, even limiting the eld to consider only the data component, is broad and complex Many of these techniques require a level of expertise that may prohibit their use in practical situations; however, a growing body of research and applications in the area of hybrid intelligent systems could address this concern Many hybrid intelligent systems have been developed in recent years Expert systems and ANNs have characteristics that can complement each other and form the basis for powerful hybrid systems Several examples of expert systems used as.

of times, out of a xed number of simulations .Any study of the performance of NNs (or any other stochastic algorithm for that matter) and any conclusions based on just one simulation are incomplete and inconclusive Conclusions on the performance of NNs must be based on the results obtained from several simulations For each simulation the NN starts with new random initial weights and uses di erent training, validation and generalization sets, independent of previous sets Performance results are then expressed as averages over all the simulations, together with variances, or con dence intervals Let denote the performance measure under consideration Results are then reported as The average is an indication of the average performance over all imulations,. Make Barcode In .NET Using Barcode creator for .NET framework .Related: Intelligent Mail Generator .NET

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High-quality EAN-13 picture output that supports all printers with djustable resolution. This encoder is extremely user-friendly with easy-to-use interface and multiple settings for the generated EAN-13, EAN-13+2, EAN-13+5 barcode images /div>. It is also named European Article Number 13, EAN/ C-13, GS1-13, GTIN-13, with variants EAN-13 Supplement 2 (a two-digit Add-On), EAN-13 Supplement 5 (a five-digit add-on).Related: Barcode Generating Excel how to, Crystal Barcode Generating , .NET Winforms Barcode Generation

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Compatible with GS1 standard for EAN-13 picture generation; Insert . If you want to know more about EAN-13 barcode size and mage, please link to the following sample codings: . EAN- 13 is also known as European Article Number 13, EAN CC-13, GS1-13, GTIN-13, with variants EAN-13 Supplement 2 (a two-digit Add-On), EAN-13 Supplement 5(a five-digit add-on).Related: Excel Barcode Generating Library, Create Barcode Word , Barcode Generation .NET Winforms C#

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compatible with Windows, consider IDAutomation's Barcode Label Software. . code,) so it is advisable to check the barcode scanner manual to make sure the .Related: 

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As we have witnessed in recent history, executives are not as well equipped to perform this responsibility as expected We advocate high focus on smart data and an accompanying strategy and management technology portfolio to improve the situation Having studied management science and operations research, we often wonder throughout our management careers why there is so little evidence that executives apply the methods and algorithms that many have learned and some of us continue to teach Upon investigation, a pattern appeared: while problem solving logic and formulations might apply, there is often insuf cient data on which to operate Data may be de cient in a variety of ways, ranging from there isn t any to a host of issues about quality Yet, mostly, de ciencies have to do with failing to prepare for and anticipate the need for data Thus we suggest that executives raise questions and demand smart data to answer those questions in order to optimize enterprise performance Answering Questions that Management Does Not Believe Could Be Answered When operating Talon Publishing & Research, a rm dedicated to answering questions that management did not believe could be answered, George conducted primary research for a new product initiative at GTE Telecom The product was a telecommunications management system that was the brainchild of retired Air Force of cers who envisioned applying what they had learned in the military combined with commercial off-the-shelf (COTS) technology to commercial needs about which they knew little Before investing, GTE executives wanted to know the market for the system and details about how to price the product and associated services By employing a 20 page research instrument mailed to 5000 individuals selected from the prospective customer universe, and with a 20% response rate, GTE determined that it could sell 50 units with high certainty, and the research provided granular information related to pricing product and service features Before the survey, many executives were skeptical You will never get them to answer 20 pages of questions To make a long tory short, success was based on presenting the right questions to a highly quali ed audience for which the questions were relevant and important to them, and we promised to share the answers Research results-driven advertising and marketing instruments were rapidly prepared immediately upon completion of the analysis Messages were closely aligned with what was learned about customers Timely follow-up was directed to the hot prospect respondents and $80 million in new business was closed within 12 months with signi cant after-sales service of >$300 million The short and ef cient selling cycle made believers of GTE management and they created the GTE Intrapreneur Program as a result, whereby the technique was routinely applied to developing ventures Today, companies employ this technique in an ever more sophisticated manner, leveraging social media, blogging, electronic white paper publishing, and surveying The more the audience is bombarded by this surfeit of information, the more creative enterprises must be to entice and engage customers Smart data is central to.

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