TRAINING OF THE PROBABILITY LOGIC NETWORKS FOR PATTERNS RECOGNITION USING ON-LINE GENETIC ALGORITHM

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SEYFIPOUR N.; MENHAJ M.B.; NIKRAVESH K.Y.

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Journal Paper

Paper Information

Journal: Daneshvar Medicine: Basic and Clinical Research Journal Year:2003 | Volume:10 | Issue:43 Page(s): 45-54

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Information Journal Paper

Title

TRAINING OF THE PROBABILITY LOGIC NETWORKS FOR PATTERNS RECOGNITION USING ON-LINE GENETIC ALGORITHM

Author(s)

SEYFIPOUR N. | MENHAJ M.B. | NIKRAVESH K.Y. | Issue Writer Certificate

Keywords

NEURAL NETWORKSQ4

PATTERN RECOGNITIONQ4

GENETICQ4

ALGORITHMSQ4

Abstract

One of the important tools has been recognized to identify patterns is the NEURAL NETWORKS and the authors have investigated the application of PLN in this article. This structure was recommended in 1989 and it's capability for simultaneously saving of each pattern, was surveyed. For training this structure, a method called "A-Learning rule" is recommended and also convergence analysis is investigated. Training of the mentioned structure. "A-Learning rule" and "On-Line GENETIC algorithm (OGA)" premier presented by authors, are used for saving 0-9 Latin digit. Higher convergence speed and capability of saving space of the OGA in compare to the A-learning rule on the PLN, are the results of this article.

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APA: Copy

SEYFIPOUR, N., MENHAJ, M.B., & NIKRAVESH, K.Y.. (2003). TRAINING OF THE PROBABILITY LOGIC NETWORKS FOR PATTERNS RECOGNITION USING ON-LINE GENETIC ALGORITHM. DANESHVAR MEDICINE, 10(43), 45-54. SID. https://sid.ir/paper/31025/en

Vancouver: Copy

SEYFIPOUR N., MENHAJ M.B., NIKRAVESH K.Y.. TRAINING OF THE PROBABILITY LOGIC NETWORKS FOR PATTERNS RECOGNITION USING ON-LINE GENETIC ALGORITHM. DANESHVAR MEDICINE[Internet]. 2003;10(43):45-54. Available from: https://sid.ir/paper/31025/en

IEEE: Copy

N. SEYFIPOUR, M.B. MENHAJ, and K.Y. NIKRAVESH, “TRAINING OF THE PROBABILITY LOGIC NETWORKS FOR PATTERNS RECOGNITION USING ON-LINE GENETIC ALGORITHM,” DANESHVAR MEDICINE, vol. 10, no. 43, pp. 45–54, 2003, [Online]. Available: https://sid.ir/paper/31025/en

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