English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper is focused on finding the optimum number of single networks in multiple neural networks combination to improve neural network model robustness for nonlinear process modeling and control. In order to improve the generalization capability of single neural network based models, combining multiple neural networks is proposed in this paper. By studying the optimum number of network that can be combined in multiple network combination, the researcher can estimate the complexity of the proposed model then obtained the exact number of networks for combination. Simple averaging combination approach is implemented in this paper which is applied to nonlinear process models. It is shown that the optimum number of networks for combination can be obtained hence enhancing the performance of the proposed model. ABSTRAK: Karya ini memberi tumpuan kepada pencarian angka optimum untuk rangkaian tunggal dalam gabungan rangkaian neural pelbagai untuk meningkatkan kemantapan model kawalan dan model proses tidak linear. Untuk meningkatkan keupayaan generalisasi model rangkaian tunggal, penggabungan rangkaian neural pelbagai telah dicadangkan dalam kertas kerja ini. Kajian bilangan optimum rangkaian tungal yang boleh digabungkan dalam gabungan rangkaian pelbagai, penyelidik boleh menganggarkan kerumitan model yang dicadangkan. Bilangan rangkaian yang tepat untuk gabungan juga boleh di kira. Pendekatan gabungan purata yang mudah berdasarkan model proses tidak linear telah di kaji dalam kertas ini. Bilangan optimum rangkaian untuk kombinasi yang

OPTIMUM NUMBERS OF SINGLE NETWORK FOR COMBINATION IN MULTIPLE NEURAL NETWORKS MODELING APPROACH FOR MODELING NONLINEAR SYSTEM