**7. References**

130 Recurrent Neural Networks and Soft Computing

**a**

10.00 10.05 10.10 10.15 10.20

0 0.12 0.24 0.36 0.48

Time(s)

This chapter proposes a time-delay recurrent neural network (TDRNN) with better performance in memory than popular neural networks by employing the time-delay and recurrent mechanism. Subsequently, the dynamic recurrent back propagation algorithm for the TDRNN is developed according to the gradient descent method. Furthermore, to train neural networks more efficiently, we propose three criterions of selecting proper learning rates for the dynamic recurrent back propagation algorithm based on the discrete-type Lyapunov stability analysis. Besides, based on the TDRNN model, we have described, analyzed and discussed an identifier and an adaptive controller designed to identify and

 a -- obtained by Senjyu b -- obtained by Shi c -- obtained in this paper

**<sup>b</sup> <sup>c</sup>**

Fig. 11. Comparison of speed control curves using different schemes

%1.1

Time(s)

%7.5

3.3

3.6

3.0

2.4

Speed (m/s)

1.2

Fig. 12. Speed control curve for step type

**5. Conclusions** 

1.8

3.4

3.5

3.6

3.7

%9.1

Speed( m/ s) 3.8


**7** 

**BRNN-SVM: Increasing the Strength of Domain** 

A protein domain is the basic unit of protein structure that can develop itself by using its own shapes and functions, and exists independently from the rest of the protein sequence. Protein domains can be seen as distinct functional or structural units of a protein. Protein domains provide one of the most valuable information for the prediction of protein structure, function, evolution, and design. Protein domain is detected from protein structure that is predicted from protein sequence of amino acid. The protein sequence may be contained of single-domain, two-domain, or multiple-domain with different or matching copies of protein domain. A protein domain comprises of protein domain boundary that relates to a part in amino acid residue where each residue in the protein chain is defined as domain position. Each shape of protein domain is a compacted and folded structure that is independently stable. It exists independently since the protein domain is a part of the protein sequence. The independent modular nature of protein domain means that it can often be found in proteins with the same domain content, but in different orders or in different proteins. The knowledge of protein

domain boundaries is useful in analysing the different functions of protein sequences.

Several methods have been developed to detect the protein domain, which can be categorized as follows: (1) Methods based on similarity and used multiple sequence alignments to represent domain boundaries, e.g. KemaDom (Lusheng et al., 2006) and Biozon (Nagaranjan

**1. Introduction** 

**Signal to Improve Protein Domain** 

*2Laboratory of Computational Intelligence and Biotechnology,* 

*Faculty of Computer Science and Information Systems* 

*Faculty of Computer Science and Information Systems* 

*Faculty of Computer Science and Information Technology* 

Kalsum U. Hassan1, Razib M. Othman2, Rohayanti Hassan2, Hishammuddin Asmuni3, Jumail Taliba2 and Shahreen Kasim4 *1Department of Information Technology, Kolej Poly-Tech MARA Batu Pahat,* 

**Prediction Accuracy** 

*Tingkat 3, Bangunan Tabung Haji, Batu Pahat,* 

*Universiti Teknologi Malaysia, UTM Skudai,* 

*Universiti Teknologi Malaysia, UTM Skudai,* 

*Universiti Tun Hussien Onn, UTHM Parit Raja,* 

*3Department of Software Engineering* 

*4Department of Web Technology,* 

*Malaysia* 

