• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.288-291
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• 2000

In ATM Network, many algorithms have been proposed for rate-based ABR new control. The object of these Algorithms is to him around from cell loss and to use the unused bandwidth by ABR Traffic. These Algorithms are applied to control ABR Traffic by EFCI and ER switches. In previous paper, we showed the using rate of bandwidth for the characteristic of each algorithm applied these algorithm network In this paper, we will do that to apply these algorithms to a network and to make a graph of characteristic of each algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.745-750
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• 2000

In ATM Network, many algorithms have been proposed for rate-based ABR flow control. The object of these Algorithms is to turn around from cell loss and to use the unused bandwidth by ABR Traffic. These Algorithms are applied to control ABR Traffic by EFCI and ER switches. In previous paper, we showed the using rate of bandwidth for the characteristic of each algorithm applied these algorithm network. In this paper, we will do that to apply these algorithms to a network and to make a graph of characteristic of each algorithm.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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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.

• Journal of Korean Society of Transportation
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• v.13 no.3
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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.

• IE interfaces
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• v.23 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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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.

• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.525-534
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• 2005

We present several distributed algorithms for localizing nodes of a wireless sensor network. Our algorithms determine locations of nodes based on the connectivity between nodes. The basic idea behind our algorithms is to estimate distances between nearby nodes by counting their common neighbors. We analyze the performance of our algorithms experimentally. The results of experiments show that our algorithms achieve performance improvements upon the existing algorithms

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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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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• v.23 no.1
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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.