Role of Feed Forward Neural Networks Coupled with Genetic Algorithm in Capitalizing of Intracellular Alpha-Galactosidase Production by <i>Acinetobacter</i> sp.

<table>Feed forward neural network design used for optimization of alpha-galactosidase production. <svg height="12.4815pt" id="M25" style="vertical-align:-0.2129993pt" version="1.1" viewbox="-0.0498162 -12.2685 21.906 12.4815" width="21.906pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M962 650H739L732 622L760 619C812 613 819 604 798 552C760 457 671 267 606 131H604L511 638H480L237 131H233L183 554C177 607 183 614 226 619L248 622L257 650H24L17 622C88 615 92 611 103 524L173 -11H203L450 491H453L543 -11H575L839 529C882 609 886 613 953 622L962 650Z" id="g113-88"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="974" vert-adv-y="974"></glyph.data></g><g transform="matrix(.0095,0,0,-0.0095,13.203,-5.984)"><path d="M870 650H600L593 618C681 609 684 605 669 516L641 367H261L286 516C302 603 313 610 391 618L398 650H132L123 618C214 610 218 606 200 516L127 130C113 46 107 40 25 32L18 0H290L298 32C204 40 200 42 214 130L250 321H631L596 131C580 47 573 39 484 32L475 0H753L762 32C673 39 668 46 685 130L757 516C772 606 778 610 861 618L870 650Z" id="g50-73"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="882" vert-adv-y="882"></glyph.data></g></svg> is weight of connection between input and hidden layer and <svg height="12.6338pt" id="M26" style="vertical-align:-0.2129993pt" version="1.1" viewbox="-0.0498162 -12.4208 20.7732 12.6338" width="20.7732pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.0135,0,0,-0.0135,0,0)"><path d="M962 650H739L732 622L760 619C812 613 819 604 798 552C760 457 671 267 606 131H604L511 638H480L237 131H233L183 554C177 607 183 614 226 619L248 622L257 650H24L17 622C88 615 92 611 103 524L173 -11H203L450 491H453L543 -11H575L839 529C882 609 886 613 953 622L962 650Z" id="g113-88"></path><glyph.data ascent="3473" descent="-2876" horiz-adv-x="974" vert-adv-y="974"></glyph.data></g><g transform="matrix(.0095,0,0,-0.0095,13.203,-5.984)"><path d="M750 359C750 550 603 667 427 667C199 667 24 499 24 287C24 100 166 -17 344 -17C573 -17 750 136 750 359ZM645 356C645 196 538 24 350 24C205 24 127 136 127 285C127 471 247 626 422 626C571 626 645 521 645 356Z" id="g50-80"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="774" vert-adv-y="774"></glyph.data></g></svg> is weight of connection between hidden and output layer.</table>

BioMed Research International

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Figure 2

Figure 2: Role of Feed Forward Neural Networks Coupled with Genetic Algorithm in Capitalizing of Intracellular Alpha-Galactosidase Production by <i>Acinetobacter</i> sp. 

Figure 2 | Role of Feed Forward Neural Networks Coupled with Genetic Algorithm in Capitalizing of Intracellular Alpha-Galactosidase Production by Acinetobacter sp. 