• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.8
• /
• pp.731-738
• /
• 2011

In this paper, we introduce an advanced architecture of K-Means clustering-based polynomial Radial Basis Function Neural Networks (p-RBFNNs) designed with the aid of SSOA (Space Search Optimization Algorithm) and develop a comprehensive design methodology supporting their construction. In order to design the optimized p-RBFNNs, a center value of each receptive field is determined by running the K-Means clustering algorithm and then the center value and the width of the corresponding receptive field are optimized through SSOA. The connections (weights) of the proposed p-RBFNNs are of functional character and are realized by considering three types of polynomials. In addition, a WLSE (Weighted Least Square Estimation) is used to estimate the coefficients of polynomials (serving as functional connections of the network) of each node from output node. Therefore, a local learning capability and an interpretability of the proposed model are improved. The proposed model is illustrated with the use of nonlinear function, NOx called Machine Learning dataset. A comparative analysis reveals that the proposed model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.

• International Journal of Highway Engineering
• /
• v.16 no.6
• /
• pp.115-120
• /
• 2014

PURPOSES : This research describes how to predict the life cycles of fatigue cracking based on NCHRP Report 704 as well as modified harmony search (MHS) algorithm. METHODS : The fatigue cracking regression model of NCHRP Report 704 was used in order to calculate the ESAL (Equivalent Single Axle Load) numbers up to pavement failure, based on using material parameters, composite modulus, and surface pavement thickness. Furthermore, the MHS algorithm was implemented to find appropriate material parameters and other structural conditions given the number of ESALs, which is related to pavement service life. RESULTS : The case studies show that the material and structural parameters can be obtained, resulting in satisfying the failure endurance of asphalt concrete structure, given the number of ESALs. For example, the required ESALs such as one or two millions are targeted to satisfy the service performance of asphalt concrete pavements in this study. CONCLUSIONS : According to the case studies, It can be concluded that the MHS algorithm provides a good tool of optimization problems in terms of minimizing the difference between the required service cycles, which is a given value, and the calculated service cycles, which is obtained from the fatigue cracking regression model.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2005.11a
• /
• pp.53-56
• /
• 2005

NTSS(New Three-Step Search Algorithm)는 대표적인 Fast BMA(Block Matching Algorithm)인 TSS(Three-Step Search Algorithm)에 중앙 편향적(Center-Biased) 특성을 고려하여 향상시킨 방법이다. 그러나 NTSS는 움직임이 작은 영상인 경우에는 TSS보다 개선된 성능을 보여주지만, 움직임이 큰 영상에 대해서는 TSS와 큰 차이가 없으며 탐색영역이 커질수록 오히려 성능이 떨어지는 단점이 있다. 본 논문에서는 움직임 벡터의 특성에 맞는 탐색영역을 적용시킴으로써 탐색영역의 증가로 발생되는 NTSS의 단점을 보완하여 움직임이 큰 영상에 대해서도 향상된 성능을 갖는 방법을 제안한다. 제안된 방법을 적용 하였을 때 움직임이 작은 영상에서는 기존의 방법과 동일한 결과를 얻었으며 움직임이 큰 영상에서는 최고 0.5dB이상 성능이 개선되었다.

• Journal of Power Electronics
• /
• v.19 no.6
• /
• pp.1566-1574
• /
• 2019

Maximum power point tracking (MPPT) under the partial shading condition is a challenging research topic for photovoltaic systems. Shaded photo-voltaic module result in complex peak patterns on the power versus voltage curve which can misguide classical MPPT algorithms. Thus, various kinds of global MPPT algorithms have been studied. These have typically consisted of partial shading detection, global peak search and MPPT. The conventional partial shading detection algorithm aims to detect all of the occurrences of partial shading. This results in excessive execution of global peak searches and discontinuous operation of the MPPT. This in turn, reduces the achievable power for the PV module. Based on a theoretical investigation of power verse voltage curve patterns under various partial shading conditions, it is realized that not all the occurrences of partial shadings require a global peak search. Thus, an intelligent partial shading detection algorithm that provides exact identification of global peak search necessity is essential for the efficient utilization of solar energy resources. This paper presents a new partial shading determinant algorithm utilizing adaptive threshold levels. Conventional methods tend to be too sensitive to sharp shading patterns but insensitive to smooth patterns. However, the proposed algorithm always shows superb performance, regardless of the partial shading patterns.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12
• /
• pp.65-74
• /
• 2021

Digital image processing and retrieving have increasingly become very popular on the Internet and getting more attention from various multimedia fields. That results in additional privacy requirements placed on efficient image matching techniques in various applications. Hence, several searching methods have been developed when confidential images are used in image matching between pairs of security agencies, most of these search methods either limited by its cost or precision. This study proposes a secure and efficient method that preserves image privacy and confidentially between two communicating parties. To retrieve an image, feature vector is extracted from the given query image, and then the similarities with the stored database images features vector are calculated to retrieve the matched images based on an indexing scheme and matching strategy. We used a secure content-based image retrieval features detector algorithm called Speeded-Up Robust Features (SURF) algorithm over public cloud to extract the features and the Honey Encryption algorithm. The purpose of using the encrypted images database is to provide an accurate searching through encrypted documents without needing decryption. Progress in this area helps protect the privacy of sensitive data stored on the cloud. The experimental results (conducted on a well-known image-set) show that the performance of the proposed methodology achieved a noticeable enhancement level in terms of precision, recall, F-Measure, and execution time.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.12-22
• /
• 2024

The travelling salesman problem is very famous and very difficult combinatorial optimization problem that has several applications in operations research, computer science and industrial engineering. As the problem is difficult, finding its optimal solution is computationally very difficult. Thus, several researchers have developed heuristic/metaheuristic algorithms for finding heuristic solutions to the problem instances. In this present study, a new hybrid genetic algorithm (HGA) is suggested to find heuristic solution to the problem. In our HGA we used comprehensive sequential constructive crossover, adaptive mutation, 2-opt search and a new local search algorithm along with a replacement method, then executed our HGA on some standard TSPLIB problem instances, and finally, we compared our HGA with simple genetic algorithm and an existing state-of-the-art method. The experimental studies show the effectiveness of our proposed HGA for the problem.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.12 no.6
• /
• pp.1-9
• /
• 2013

The studies on the shortest path algorithms based on Dijkstra algorithm has been done continuously to decrease the time for searching. $A^*$ algorithm is the most represented one. Although fast searching speed is the major point of $A^*$ algorithm, there are high rates of failing in search of the shortest path, because of complex and irregular networks. The failure of the search means that it either did not find the target node, or found the shortest path, witch is not true. This study proposed $A^*$ algorithm applying method that can reduce searching failure rates, preferentially organizing the relations between the starting node and the targeting node, and appling it in reverse according to the organized path. This proposed method may not build exactly the shortest path, but the entire failure in search of th path would not occur. Following the developed algorithm tested in a real complex networks, it revealed that this algorithm increases the amount of time than the usual $A^*$ algorithm, but the accuracy rates of the shortest paths built is very high.

• Proceedings of the KSME Conference
• /
• 2007.05b
• /
• pp.2476-2481
• /
• 2007

An inverse radiation analysis is presented for the estimation of the wall emissivities for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. In this study, a repulsive particle swarm optimization(RPSO) algorithm which is a relatively recent heuristic search method is proposed as an effective method for improving the search efficiency for unknown parameters. To verify the performance of the proposed RPSO algorithm, it is compared with a basic particle swarm optimization(PSO) algorithm and a hybrid genetic algorithm(HGA) for the inverse radiation problem with estimating the wall emissivities in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. A finite-volume method is applied to solve the radiative transfer equation of a direct problem to obtain measured temperatures.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.14 no.5
• /
• pp.499-505
• /
• 2003

In the design of mobile wireless communication system, base station location is one of the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively fur global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.5
• /
• pp.1218-1224
• /
• 2008

Located on the upstream of a gene, the promoter region that plays a very important role in the control of gene expression as a signal part has various binding sites for transcription factors. These binding sites are present in various parts of the promoter region and assume an aspect of highly conserved consensus sequence pattern. This paper deals with the introductions of search methods for consensus pattern, including Wataru method, EM algorithm, MEME algorithm, Genetic algorithm and Phylogenetic Footprinting method, and intends to give future prospects of research on this field.