Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S)
Inspired by ARPOP-CRI(S) (Appetitive Reward-based Pseudo-Outer-Product Fuzzy Neural Network), a sequential learning model that incorporates the concepts of pre-synaptic and synaptic inspirations in Aplysia feeding behaviour, the student decided to build a new computational model that supports both s...
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| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/10356/48898 |
| _version_ | 1811692175101001728 |
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| author | Do, The Anh |
| author2 | Quek Hiok Chai |
| author_facet | Quek Hiok Chai Do, The Anh |
| author_sort | Do, The Anh |
| collection | NTU |
| description | Inspired by ARPOP-CRI(S) (Appetitive Reward-based Pseudo-Outer-Product Fuzzy Neural Network), a sequential learning model that incorporates the concepts of pre-synaptic and synaptic inspirations in Aplysia feeding behaviour, the student decided to build a new computational model that supports both structure learning as well as parameter learning in an online learning process. The model are constructed with preservation of features that support ARPOP-CRI(S) to deal with di culties in processing dynamic data stream as well as novel points that help the model with a better generality and performance.
The model is evaluated and compared with several established works. Experimental results from benchmark applications support the model with promising results. The model is observed working well in a number of elds which include time-varying signal detection, forecasting, nonlinear control and de-cision support. The model is also tested extensively in real nancial market data.
This report is the documentation representing steps and research taken as well as results recorded by the student in the course of accomplishing the project. |
| first_indexed | 2024-10-01T06:31:36Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/48898 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:31:36Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/488982023-03-03T20:49:04Z Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) Do, The Anh Quek Hiok Chai School of Computer Engineering Cheu Eng Yeow DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Inspired by ARPOP-CRI(S) (Appetitive Reward-based Pseudo-Outer-Product Fuzzy Neural Network), a sequential learning model that incorporates the concepts of pre-synaptic and synaptic inspirations in Aplysia feeding behaviour, the student decided to build a new computational model that supports both structure learning as well as parameter learning in an online learning process. The model are constructed with preservation of features that support ARPOP-CRI(S) to deal with di culties in processing dynamic data stream as well as novel points that help the model with a better generality and performance. The model is evaluated and compared with several established works. Experimental results from benchmark applications support the model with promising results. The model is observed working well in a number of elds which include time-varying signal detection, forecasting, nonlinear control and de-cision support. The model is also tested extensively in real nancial market data. This report is the documentation representing steps and research taken as well as results recorded by the student in the course of accomplishing the project. Bachelor of Engineering (Computer Science) 2012-05-10T07:59:21Z 2012-05-10T07:59:21Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48898 en Nanyang Technological University 64 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Do, The Anh Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title | Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title_full | Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title_fullStr | Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title_full_unstemmed | Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title_short | Structural evolving appetitive reward-based pseudo-outer-product fuzzy neural network SE-ARPOP-CRI(S) |
| title_sort | structural evolving appetitive reward based pseudo outer product fuzzy neural network se arpop cri s |
| topic | DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | http://hdl.handle.net/10356/48898 |
| work_keys_str_mv | AT dotheanh structuralevolvingappetitiverewardbasedpseudoouterproductfuzzyneuralnetworksearpopcris |