• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.977.1-1000
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• 1993

This paper presents a fuzzy neural network, called the fuzzy counterpropagation network, that structures its inputs and generates its outputs in a manner based on counterpropagation networks. The fuzzy counterpropagation network is developed by incorporating the concept of fuzzy clustering into the hidden layer responses. Three learning algorithms are introduced for use with the proposed network. Simulations demonstrate that fuzzy counterpropagation networks with the proposed learning algorithms work well on approximating bipolar and continuous functions.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2000년도 추계종합학술대회
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• pp.288-291
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• 2000

ATM 망에서는 전송률 기반의 ABR 흐름제어를 위해 다수의 알고리즘들이 제안되고 있다. 이 알고리즘들의 주 목적은 셀 손실률을 회피하고 미사용중인 대역폭을 ABR 트래픽에 의해 사용되게 하는 것이다. 이러한 알고리즘들은 EFCI와 ER 스위치에서 동작하여 ABR 트래픽을 재어하는데 사용된다. 이전 논문에서 이러한 스위치 알고리즘들을 network에 적용하여 각 알고리즘들의 성능에 의한 대역 이용률을 도시하였다. 본 논문에서는 이의 보완을 위해 각 알고리즘들의 셀 손실률과 회선 이용률을 도시하여 그 성능을 비교, 분석하고자 한다.

• 한국정보통신학회논문지
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• 제4권4호
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• pp.745-750
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• 2000

ATM 망에서는 전송률 기반의 ABR 흐름제어를 위해 다수의 알고리즘들이 제안되고 있다. 이 알고리즘들의 주 목적은 셀 손실률을 회피하고 미사용중인 대역폭을 ABR 트래픽에 의해 사용되게 하는 것이다. 이러한 알고리즘들은 EFCI와 ER 스위치에서 동작하여 ABR 트래픽을 제어하는데 사용된다. 이전 논문에서 이러한 스위치 알고리즘들을 network에 적용하여 각 알고리즘들의 성능에 의한 대역 이용률을 도시하였다. 본논문에서는 이의 보완을 위해 각 알고리즘들의 셀 손실률과 회선 이용률을 도시하여 그 성능을 비교, 분석하고자 한다.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.170-178
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• 2024

Through the growth of the fifth-generation networks and artificial intelligence technologies, new threats and challenges have appeared to wireless communication system, especially in cybersecurity. And IoT networks are gradually attractive stages for introduction of DDoS attacks due to integral frailer security and resource-constrained nature of IoT devices. This paper emphases on detecting DDoS attack in wireless networks by categorizing inward network packets on the transport layer as either "abnormal" or "normal" using the integration of machine learning algorithms knowledge-based system. In this paper, deep learning algorithms and CNN were autonomously trained for mitigating DDoS attacks. This paper lays importance on misuse based DDOS attacks which comprise TCP SYN-Flood and ICMP flood. The researcher uses CICIDS2017 and NSL-KDD dataset in training and testing the algorithms (model) while the experimentation phase. accuracy score is used to measure the classification performance of the four algorithms. the results display that the 99.93 performance is recorded.

• 대한교통학회지
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• 제13권3호
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• pp.35-52
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• 1995

This paper reviews both network representation schemes of transportation network and algorithms for findings the shortest path between two points in the network. Two types of network representation schmes for considering U-Turn have been proposed along with some modifications of the vine-based Dijkstra shoretest path algorithm. The traditional Sioux-Fall network has been chosen and modified with the introduction of left-turn prohibitions and U-Turns for the purpose of evaluating the peroformance of two modified algorithms and network representation schemes(NA1 an d NA2 ). This type of modification in both network representation scheme (including network data) and algorithms is not only supposed to be needed for route guidance but supposed to contribute to finding more realistic path and estimating more accurate traffic voulume thorughout the entire network.

• 산업공학
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• 제23권1호
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• pp.24-34
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• 2010

In the telecommunication system which is based on the existing PSTN(public switched telephone network), feature interaction has been an important research issue in order to provide seamless services to users. Recently, rapid proliferation of IP-based network and the various types of IP media supply services, the feature interaction from the perspective of application services has become a significant aspect. This paper presents conflict detection and resolution algorithms for designing and operating a variety of services that are provided through IP-based network. The algorithms use explicit service interactions to detect conflicts between a new service and registered services. They then apply various rules to reduce search space in resolving conflicts. The algorithms are applied to a wide range of realistic service provision scenarios to validate that it can detect conflicts between services and resolve in accordance with different rule sets. By applying the algorithms to various scenarios, it is observed that the proposed algorithms can be effectively used in operating an IP-based services network.

• 제어로봇시스템학회논문지
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• 제9권1호
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• pp.57-62
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• 2003

It is difficult to determine the feeding rate of coagulant in the water treatment plant, due to nonlinearity, multivariables and slow response characteristics etc. To deal with this difficulty, the genetic-fuzzy system genetic-equation system and the neural network system were used in determining the feeding rate of the coagulant. Fuzzy system and neural network system are excellently robust in multivariables and nonlinear problems. but fuzzy system is difficult to construct the fuzzy parameter such as the rule table and the membership function. Therefore we made the genetic-fuzzy system by the fusion of genetic algorithms and fuzzy system, and also made the feeding rate equation by genetic algorithms. To train fuzzy system, equation parameter and neural network system, the actual operation data of the water treatment plant was used. We determined optimized feeding rates of coagulant by the fuzzy system, the equation and the neural network and also compared them with the feeding rates of the actual operation data.

• 정보처리학회논문지C
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• 제12C권4호
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• pp.525-534
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• 2005

본 논문에서는 무선 센서 네트워크 상에서 노드들 간의 연결성만을 이용하여 노드의 위치를 추정하는 분산 알고리즘을 제안한다. 본 논문에서 제안하는 알고리즘들은 기본적으로 공통 인접 노드의 개수를 이용하여 인접한 두 노드간의 거리를 추정하는 기법에 기반하고 있다. 제안된 알고리즘들의 위치 추정 성능을 모의실험을 통하여 분석 비교하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권1호
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• pp.145-164
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• 2014

Network virtualization provides a promising tool to allow multiple heterogeneous virtual networks to run on a shared substrate network simultaneously. A long-standing challenge in network virtualization is the Virtual Network Embedding (VNE) problem: how to embed virtual networks onto specific physical nodes and links in the substrate network effectively. Recent research presents several heuristic algorithms that only consider single topological attribute of networks, which may lead to decreased utilization of resources. In this paper, we introduce six complementary characteristics that reflect different topological attributes, and propose three topology-aware VNE algorithms by leveraging the respective advantages of different characteristics. In addition, a new KS-core decomposition algorithm based on two characteristics is devised to better disentangle the hierarchical topological structure of virtual networks. Due to the overall consideration of topological attributes of substrate and virtual networks by using multiple characteristics, our study better coordinates node and link embedding. Extensive simulations demonstrate that our proposed algorithms improve the long-term average revenue, acceptance ratio, and revenue/cost ratio compared to previous algorithms.

• International Journal of Computer Science & Network Security
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• 제23권1호
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• pp.164-168
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• 2023

As our community has become increasingly dependent on technology, security has become a bigger concern, which makes it more important and challenging than ever. security can be enhanced with encryption as described in this paper by combining RC6 symmetric cryptographic algorithms with RSA asymmetric algorithms, as well as the Vigenère cipher, to help manage weaknesses of RC6 algorithms by utilizing the speed, security, and effectiveness of asymmetric algorithms with the effectiveness of symmetric algorithm items as well as introducing classical algorithms, which add additional confusion to the decryption process. An analysis of the proposed encryption speed and throughput has been conducted in comparison to a variety of well-known algorithms to demonstrate the effectiveness of each algorithm.