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NeuroSolutions

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132: 66: 25: 531:). Given this problem type and the size of the user's data set, the Neural Expert automatically selects the neural network size and architecture that will likely produce a good solution. A beginner setting also exists which hides some of the more advanced operations such as cross validation and genetic optimization. 539:
NeuroSolutions is based on the concept that neural networks can be broken down into a fundamental set of neural components. Individually these components are relatively simplistic, but several components connected together can result in networks capable of solving very complex problems. The network
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construction wizards will connect these components based on the user's specifications. However, once the network is built, the interconnections can be arbitrarily changed and components can be added or removed. NeuroSolutions also allows for the integration of algorithms through
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This technology provides the ability to programmatically control NeuroSolutions from any external application that supports automation, such as Microsoft Excel, Microsoft Access, and applications developed with Visual Basic or
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source code for a neural network designed within its graphical user interface. This provides the flexibility to customize the neural network code for that particular application. Since the generated code is
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Once the neural network architecture is selected, the user can customize parameters such as the number of hidden layers, the number of processing elements and the learning algorithm. A
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The NeuralBuilder centers the design specifications on the specific neural network architecture the user wishes to build. Some of the most common architectures include:
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operations. From the Data Manager, the user can load the data directly into a NeuroSolutions breadboard or use the data to create a new neural network.
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The Custom Solution Wizard is an optional add-on product that will take a neural network designed within NeuroSolutions and encapsulate it into a
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The Neural Expert centers the design specifications around the type of problem the user would like the neural network to solve (
153: 38: 204: 157: 176: 454: 466: 448: 183: 142: 91: 548:. To add a new component, modify the template function for the base component and then compile the code into a DLL. 516: 372: 161: 146: 557: 478: 392: 356: 348: 336: 190: 545: 484: 380: 301: 172: 524: 496: 376: 440: 431: 364: 610: 590: 541: 606: 472: 360: 296: 44: 412: 593:(DLL) that conforms to a simple protocol. The DLL can then be embedded into the user's own C++, 544:(DLL). Every NeuroSolutions component implements a function conforming to a simple protocol in 504: 289: 87: 635: 602: 528: 404: 308: 284: 197: 347:) network design interface with an implementation of advanced learning procedures, such as 598: 408: 344: 577:-compliant, the user can deploy the neural network solution to other platforms such as 355:, and back-propagation through time. The software is used to design, train, and deploy 340: 277: 649: 416: 623: 594: 560:
solution for applications: code generation, DLL generation, and OLE generation.
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NeuroDimension, Inc. provides three ways for NeuroSolutions to deploy a custom
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NeuroSolutions provides three separate wizards for automatically building
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The Data Manager module allows the user to import data from
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can also be used to automatically optimize the settings.
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It combines a modular, icon-based ( 339:development environment developed by 7: 158:adding citations to reliable sources 387:Neural network construction wizards 411:or text files and perform various 14: 461:General regression neural network 34:This article has multiple issues. 260: 130: 64: 23: 42:or discuss these issues on the 1: 455:Radial basis function network 353:Levenberg-Marquardt algorithm 266:SVM Network in NeuroSolutions 535:User-defined neural networks 467:Probabilistic neural network 449:Principal component analysis 383:and time-series prediction. 672: 479:Time-lag recurrent network 552:Neural network deployment 357:artificial neural network 259: 485:Recurrent neural network 656:Neural network software 437:Generalized feedforward 381:multivariate regression 325:NeuroSolutions homepage 302:Neural network software 542:dynamic link libraries 525:function approximation 497:Support vector machine 377:function approximation 316:, Educational Discount 441:Modular (programming) 432:Multilayer perceptron 365:unsupervised learning 96:neutral point of view 591:dynamic link library 154:improve this article 473:Self-organizing map 361:supervised learning 349:conjugate gradients 256: 88:promotional content 90:and inappropriate 505:genetic algorithm 330: 329: 290:Microsoft Windows 252: 251: 244: 234: 233: 226: 208: 124: 123: 116: 57: 663: 636:Machine learning 603:Microsoft Access 489:CANFIS network ( 405:Microsoft Access 285:Operating system 264: 257: 247: 240: 229: 222: 218: 215: 209: 207: 173:"NeuroSolutions" 166: 134: 126: 119: 112: 108: 105: 99: 77:an advertisement 68: 67: 60: 49: 27: 26: 19: 671: 670: 666: 665: 664: 662: 661: 660: 646: 645: 644: 632: 619: 599:Microsoft Excel 587: 566: 564:Code generation 554: 537: 513: 425: 409:Microsoft Excel 401: 389: 345:component-based 267: 248: 237: 236: 235: 230: 219: 213: 210: 167: 165: 151: 135: 120: 109: 103: 100: 81: 69: 65: 28: 24: 17: 12: 11: 5: 669: 667: 659: 658: 648: 647: 643: 640: 639: 638: 631: 628: 618: 617:OLE automation 615: 586: 585:DLL generation 583: 565: 562: 558:neural network 553: 550: 536: 533: 517:classification 512: 509: 501: 500: 494: 487: 482: 476: 470: 464: 458: 452: 446: 443: 438: 435: 424: 421: 400: 397: 393:neural network 388: 385: 373:classification 341:NeuroDimension 337:neural network 333:NeuroSolutions 328: 327: 322: 318: 317: 311: 305: 304: 299: 293: 292: 287: 281: 280: 278:NeuroDimension 275: 269: 268: 265: 255:NeuroSolutions 250: 249: 232: 231: 138: 136: 129: 122: 121: 92:external links 72: 70: 63: 58: 32: 31: 29: 22: 15: 13: 10: 9: 6: 4: 3: 2: 668: 657: 654: 653: 651: 641: 637: 634: 633: 629: 627: 625: 616: 614: 612: 608: 605:or Internet ( 604: 600: 596: 592: 584: 582: 580: 576: 571: 563: 561: 559: 551: 549: 547: 543: 534: 532: 530: 526: 522: 518: 511:Neural Expert 510: 508: 506: 498: 495: 492: 488: 486: 483: 480: 477: 474: 471: 468: 465: 462: 459: 456: 453: 450: 447: 444: 442: 439: 436: 433: 430: 429: 428: 423:NeuralBuilder 422: 420: 418: 417:data analysis 414: 413:preprocessing 410: 406: 398: 396: 394: 386: 384: 382: 378: 374: 370: 366: 362: 358: 354: 350: 346: 342: 338: 334: 326: 323: 319: 315: 312: 310: 306: 303: 300: 298: 294: 291: 288: 286: 282: 279: 276: 274: 270: 263: 258: 246: 243: 228: 225: 217: 206: 203: 199: 196: 192: 189: 185: 182: 178: 175: –  174: 170: 169:Find sources: 163: 159: 155: 149: 148: 144: 139:This article 137: 133: 128: 127: 118: 115: 107: 97: 93: 89: 85: 79: 78: 73:This article 71: 62: 61: 56: 54: 47: 46: 41: 40: 35: 30: 21: 20: 620: 595:Visual Basic 588: 567: 555: 538: 514: 502: 445:Jordan/Elman 426: 402: 399:Data Manager 390: 332: 331: 273:Developer(s) 238: 220: 214:October 2023 211: 201: 194: 187: 180: 168: 152:Please help 140: 110: 101: 86:by removing 82:Please help 74: 50: 43: 37: 36:Please help 33: 611:programming 491:Fuzzy logic 369:data mining 642:References 624:Visual C++ 529:clustering 521:prediction 184:newspapers 104:March 2023 84:improve it 39:improve it 141:does not 45:talk page 650:Category 630:See also 613:skills. 395:models: 321:Website 309:License 198:scholar 162:removed 147:sources 481:(TLRN) 463:(GRNN) 351:, the 200:  193:  186:  179:  171:  499:(SVM) 475:(SOM) 469:(PNN) 457:(RBF) 451:(PCA) 434:(MLP) 335:is a 205:JSTOR 191:books 579:UNIX 575:ANSI 415:and 363:and 314:EULA 297:Type 177:news 145:any 143:cite 607:ASP 570:C++ 527:or 156:by 652:: 601:, 597:, 581:. 523:, 519:, 407:, 379:, 375:, 371:, 48:. 546:C 493:) 359:( 245:) 239:( 227:) 221:( 216:) 212:( 202:· 195:· 188:· 181:· 164:. 150:. 117:) 111:( 106:) 102:( 98:. 80:. 55:) 51:(

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Developer(s)
NeuroDimension
Operating system
Microsoft Windows
Type
Neural network software

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