論文 - 山森 一人
-
DNA塩基配列からのエクソン領域の抽出法 : マルチモーダルニューラルネットワークの開発
上舞 慶幸, 吉原 郁夫, 山森 一人, 安永 守利
インテリジェント・システム・シンポジウム講演論文集 = FAN Symposium : fuzzy, artificial intelligence, neural networks and computational intelligence 12 385 - 390 2002年11月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：一般社団法人日本機械学会
Human genome consists of 3 billion base pairs, which are divided into several kinds of regions for example promoter, exon, and intron. Exons are the protein-coding DNA sequence, but introns are not. It is important to extract exons efficiently. This paper presents a multi-modal neural network to identify exon-intron boundaries and intron-exon boundaries in DNA sequences. The multi-modal neural network is composed several multi-layer neural networks and a judgment module, and gives the best identification rate (Sensitivity : Sn) 97.1%.
-
GP Based Method for Identifying Exon Region in DNA Sequences 査読あり
T.Ohta, I.Yoshihara, K.Yamamori,M.Yasunaga
Proc. The 4th Asia- Pacific Conference on Simulates Evolution and Learning crl1333 2002年11月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
Genetic Algorithm Approach to University Timetabling 査読あり
N.Koizumi, K.Yamamori, I.Yoshihara
Proc. The 4th Asia- Pacific Conference on Simulates Evolution and Learning, crl341(CD-ROM) crl-1341 2002年11月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
Compound Defect Compensation on Multi-Layer Neural Networks by Partial Retraining Scheme 査読あり
K.Yamamori, T.Abe, S.Horiguchi,I.Yoshihara
Proc. The Third International Conference on Parallel and Distributed Computing, Applications and Technologies 403 - 408 2002年9月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
A GA-based method for multiple protein sequence alignment
Nguyen Hung Dinh, Yoshihara Ikuo, Yamamori Kunihito, Yasunaga Moritoshi
宮崎大學工學部紀要 31 347 - 354 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
This paper presents a parallel hybrid genetic algorithm (GA) for solving the sum-of-pairs multiple protein sequence alignment. A new chromosome representation and its corresponding genetic operators are proposed. A multi-population GENITOR-type GA is combined with local search heuristics. It is then extended to run in parallel on a multiprocessor system for speeding up. Experimental results of benchmarks from the BAliBASE show that the proposed method is superior to MSA, OMA, and SAGA methods with regard to quality of solution and running time. It can be used for finding multiple sequence alignment as well as testing cost functions.
-
Evaluation of GP-based time series prediction
Ohta Takehiro, Yoshihara Ikuo, Yamamori Kunihito, Yasunaga Moritoshi
宮崎大學工學部紀要 31 325 - 330 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
Development of a multi-modal nueral network for predicting protein secondary structure
Zhu Hanxi, Yoshihara Ikuo, Yamamori Kunihito, Yasunaga Moritoshi
宮崎大學工學部紀要 31 331 - 338 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
Comparison with defect compensation methods for freed-forward neural networks
Yamamori Kunihito, Takahashi Kinya, Yoshihara Ikuo
宮崎大學工學部紀要 31 379 - 383 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
A parallel greedy GA for symmetric and asymmetric TSPs
Nguyen Hung Dinh, Yoshihara Ikuo, Yamamori Kunihito, Yasunaga Moritoshi
宮崎大學工學部紀要 31 339 - 346 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
Timetabling for University Classes using Genetic Algorithm
Yoshihara Ikuo, Koizumi Naoki, Yamamori Kunihito
宮崎大學工學部紀要 31 355 - 360 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
Research on identifying intron-exon boundaries in DNA sequences
Kamimai Yoshiyuki, Yoshihara Ikuo, Yamamori Kunihito, Yasunaga Moritoshi
宮崎大學工學部紀要 31 313 - 318 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
免疫機構を導入した遺伝的アルゴリズムによる巡回セールスマン問題の解法
吉原 郁夫, 森重 伸也, 山森 一人
宮崎大學工學部紀要 31 319 - 324 2002年7月
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：宮崎大学
-
Prediction of Protein Secondary Structure by Multi-Modal Neural Networks 査読あり
H.Zhu, I.Yoshihara, K.Yamamori
Proc. International Joint Conference on Neural Networks 280 - 285 2002年5月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
A Parallel Hybrid Genetic Algorithm for Multiple Protein Sequence Alignment 査読あり
H.D.Nguyen, I.Yoshihara,K.Yamamori, M.Yasunaga
Proc. Congress on Evolutionary Computation 309 - 314 2002年5月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
An Efficient Defect Compensation Scheme for Multi-Layer Neural Networks on WSI Devices 査読あり
K.Yamamori, T.Abe, S.Horiguchi, I.Yoshihara
Proc. International Joint Conference on Neural Networks 1056 - 1061 2002年5月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）
-
A parallel hybrid genetic algorithm for multiple protein sequence alignment
Nguyen H., Yoshihara I., Yamamori K., Yasunaga M.
Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002 1 309 - 314 2002年
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
This paper presents a parallel hybrid genetic algorithm (GA) for solving sum-of-pairs multiple protein sequence alignment. The method is based on a multiple population GENITOR-type GA and involves local search heuristics. It is then extended to parallel to exploit the benefit of a multiprocessor system. Benchmarks from the BAliBASE library are used to validate the method. © 2002 IEEE.
-
Comparison of defect compensation methods for feedforward neural networks
Takahashi K., Horiguchi S., Yamamori K., Yoshihara I.
Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC 2002-January 293 - 300 2002年
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of IEEE Pacific Rim International Symposium on Dependable Computing, PRDC
© 2002 IEEE. Recently, many defect compensation methods have been proposed for feedforward neural networks implemented in hardware devices. However, there are few accurate quantitative comparisons with the performance of these defect compensation methods. In this paper, we compare the following three defect compensation methods; partial retraining (PR) scheme, whole network backpropagation (BP) retraining and FT (fault-tolerant) BP method. The BP algorithm and PR scheme retrain the neural network after defects have occurred. The FTBP method tries to obtain the weights those are robust for the defects. We can say that both the BP algorithm and PR scheme are cure-type compensation methods and the FTBP method is a precaution-type compensation method. We compare the average recognition rate, average training time and the generalization ability among these three methods in detail. The experiments show that the whole network retraining by the BP algorithm has the highest reliability on the XOR problem and face image recognition problem on the neural networks with a single broken link defect and two broken link defects.
-
An efficient defect compensation scheme for multi-layer neural networks on WSI devices
Yamamori K., Abe T., Horiguchi S., Yoshihara I.
Proceedings of the International Joint Conference on Neural Networks 1 1056 - 1061 2002年
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Proceedings of the International Joint Conference on Neural Networks
This paper discusses on high speed off-line defect compensation scheme for trained multi-layer neural networks implemented in WSI devices. Since partial retraining scheme utilizes the redundancy of neural networks, no additional circuits is needed. The performance of partial retraining scheme will be compared with that by back-propagation algorithm on face image recognition problem.
-
Aligning multiple protein sequences by parallel hybrid genetic algorithm.
Nguyen H., Yoshihara I., Yamamori K., Yasunaga M.
Genome informatics. International Conference on Genome Informatics 13 123 - 132 2002年
記述言語：日本語 掲載種別：研究論文（学術雑誌） 出版者・発行元：Genome informatics. International Conference on Genome Informatics
This paper presents a parallel hybrid genetic algorithm (GA) for solving the sum-of-pairs multiple protein sequence alignment. A new chromosome representation and its corresponding genetic operators are proposed. A multi-population GENITOR-type GA is combined with local search heuristics. It is then extended to run in parallel on a multiprocessor system for speeding up. Experimental results of benchmarks from the BAliBASE show that the proposed method is superior to MSA, OMA, and SAGA methods with regard to quality of solution and running time. It can be used for finding multiple sequence alignment as well as testing cost functions.
-
Performance Evaluation of a Partial Retraining Scheme for Defective Multi-Layer Neural Networks 査読あり
K.Yamamori, T.Abe, S.Horiguchi
Proc. 6th Australasian Computer Systems Architecture Conference 138 - 145 2001年1月
記述言語：英語 掲載種別：研究論文（国際会議プロシーディングス）