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Since the code for the bottom predictor model is almost identical to that of the timereversed Slow %K model, only the two blocks that contain changed code are presented above. In the first block of code, the time-reversed Slow %K is not used. Instead, a series of ones or zeros is calculated that indicates the presence (1) or absence (0) of bottoms (bottom target). When writing the facts, instead of writing the time-reversed Slow %K, the bottom target is written. In the second block of code, the roles for comparing the neural output with an appropriate threshold, and generating the actual entry buy signals, are implemented. In both blocks, code is included to prevent the writing of facts, or use of predictions, when tomorrow s open could not possibly be a bottom. Similar code fragments for the top predictor model appear below.

page and a volume-pricing deal The purchasing of cer agrees to give the special address of this Dell Web page to all employees who want to buy computer products It takes Dell only 30 minutes to create a new Premier Page for a new business customer When an employee comes to the site, he registers as being an employee and purchases whatever he needs, providing the Dell site with the purchase order number Every month the purchasing of cer gets a report from Dell showing which of her employees have made purchases and what they have bought She has complete information about what her rm is buying from Dell, who is buying it, and what each employee bought These reports are very useful for a purchasing department They also show the savings that the company has made through its volume deal with Dell.

Test Methodology for the Turning-Point Model The test methodology for this model is identical to that used for the time-reversed Slow %K model. The fact set is generated, loaded into N-TRAIN, scaled, and shuffled. A series of nets (from 3. to 4-layer ones) are trained to maximum convergence and then polished. Statistics such as shrinkage-corrected correlations are calculated. Training Results for the Turning-Point Model Bo&vn Forecaster. The structure of Table 1 l-2 is identical to that of Table 11-l. As with the net trained to predict the time-reversed Slow %K, there was a monotonic relationship between the number of connections in the network and the multiple correlation of the network s output with the target; i.e., larger nets evinced higher correlations. The net was trained on a total of 23,900 facts, which is a smaller fact set than that for the time-reversed Slow %K. The difference in number of facts resulted because the only facts used were those that contained some uncertainty about whether tomorrow s open could be a turning point. Since the facts for the bottom forecaster came from more widely spaced points in the time series, it was assumed that there would be less redundancy among them. When corrected for shrinkage, effective sample sizes of 23,919 (equal to the actual number of facts) and 8,000 (a reduced effective fact count) were assumed. In terms of the more severely adjusted correlations, the best net in this model appeared to be the largest 4-layer network; the smaller 4-layer network was also very good. Other than these two nets, only the 3.layer network with 10 middle-layer neurons was a possible choice. For tests of trading performance, the large 4-layer network (nn9.nef) and the much smaller 3-layer network (n&.net) were selected.

Dell has set up tens of thousands of these business-to-business pages They give Dell a tremendous advantage in business sales Today, all of Dell s competitors are copying the system and are trying to catch up The Dell system gives the business customer a lot of information Dell has put 54,000 pages of service information on the Web, and this can be accessed by any customer at any time The Premier Page lets the customer know where any given system is in the production process Dell prepares for the order s arrival by sending shipment information automatically by email Once the system arrives, the customer can troubleshoot and upgrade it online Getting companies to use the Dell Premier Page system is not always easy When Dell tried to get Eastman Chemical to use a Dell Premier Page for ordering, Eastman at rst refused, saying it was too much work.

T A B L E 11-Z -,.

Most Americans generally get too many omega-6 fatty acids and not enough omega-3 fatty acids. Following is a good formula for achieving a balance of not only omega-3 and omega-6 essential fatty acids, but omega-9 fatty acids as well. Rosemary extract, vitamin E, and ascorbyl palmitate are added to prevent rancidity and extend shelf life.