• International Journal of Advanced Culture Technology
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• 제1권2호
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• pp.1-6
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• 2013

In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

• Journal of applied mathematics & informatics
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• 제23권1_2호
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• pp.547-552
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• 2007

In this note, we extends some of the results of Liu [Fuzzy Sets and systems 157 (2006) 869-878]. This extension consists of a simple proof involving weighted functions and their preference index. We also give an elementary simple proof of the maximum entropy weighting function problem with a given preference index value without using any advanced theory like variational principles or without using Lagrangian multiplier methods.

• 한국정보과학회논문지:소프트웨어및응용
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• 제29권4호
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• pp.248-257
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• 2002

군집화는 객체들의 특성을 분석하여 유사한 성질을 갖고 있는 객체들을 동일한 집단으로 분류하는 방법이다. 전자 상거래 자료처럼 차원 수가 많고 누락 값이 많은 자료의 경우 입력 자료의 차원축약, 잡음제거를 목적으로 SVD를 사용하여 군집화를 수행하는 것이 효과적이지만, SVD를 통해 변환된 자료는 원래의 속성 정보를 상실하기 때문에 군집 결과분석에서 원본 속성의 가치 해석이 어렵다. 따라서 본 연구는 군집화 수행 후 엔트로피 가중치 및 SVD를 이용하여 군집의 중요한 속성을 발견하기 위한 군집 특징 선택 기법 ENTROPY-SVD를 제안한다. ENTROPY-SVD는 자료의 속성들과 유사객체 군과의 묵시적인 은닉 구조를 활용하기 위하여 SVD를 이용하고 유사객체 군에 포함된 응집도가 높은 속성들을 발견하기 위하여 엔트로피 가중치를 사용한다. 또한 ENTROPY-SVD를 적용한 모델 기반의 협력적 여과기법의 추천 시스템 CFS-CF를 제안하고 그 효용성 및 효과를 평가한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4611-4624
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• 2020

Future network scenario will be a heterogeneous wireless network environment composed of multiple networks and multimode terminals (MMT). Seamless switching and optimal connectivity for MMT among different networks and different services become extremely important. Here, a vertical handoff algorithm combined an improved entropy weighting method based on grey relational analysis (GRA) is proposed. In which, the improved entropy weight method is used to obtain the objective weights of the network attributes, and GRA is done to rank the candidate networks in order to choose the best network. Through simulation and comparing the results with other vertical handoff decision algorithms, the number of handoffs and reversal phenomenon are reduced with the proposed algorithm, which shows a better performance.

• 한국구조물진단유지관리공학회 논문집
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• 제21권5호
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• pp.83-93
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• 2017

본 연구에서는 보강토 옹벽 점검 자료를 바탕으로 보강토 옹벽의 상태평가항목의 가중치를 새롭게 제안하고 결함점수 및 결함지수를 제안하였다. 161개소의 보강토 옹벽의 점검결과를 근거로 다중회귀분석과 엔트로피 기법을 이용하여 상태평가항목별 가중치를 산정하였으며, 또한 전문가를 대상으로 AHP 기법을 활용하여 평가항목별 가중치를 산정하였다. 각 기법에서 도출된 가중치를 활용하여 혼한 가중치를 제안하였으며, 제안 가중치를 토대로 결함점수 및 결함지수를 제안하여 기존 161개소 현장에 적용하여 현재의 가중치와 제안 가중치에 의한 현장별 위험도 순위를 비교 분석하였다. 다중회귀분석, AHP 기법, 엔트로피 기법을 활용하여 분석한 결과 상태평가항목의 가중치 순위가 변동이 컸으며, 현재 상태평가항목의 가중치와 달리 가중치 순위의 중복은 발생하지 않았다. 특히, 다중회귀분석 결과에서는 특정 상태평가항목이 전체 가중치의 70% 이상을 차지하는 결과가 도출되었다. 제안한 혼합 가중치를 기존 보강토 옹벽 데이터에 적용한 결과, 상태평가항목의 가중치 중복은 발생하지 않았으며, 대상 보강토 옹벽 161 개소 중 16 개소의 위험도 순위 상승과 31 개소의 위험도 하락이 발생하였다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2013년도 하계학술대회
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• pp.1-2
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• 2013

KLT-AECQ 는 지각적인 성능 향상을 위하여 formant weighting 필터를 사용한다.Code Excited Linear Prediction(CELP) 코더는 사람의 음성신호를 압축하는 대표적인 방식이다. CELP 의 Rate-Distortion 성능을 향상 시키기 위해서 Karhunen-Loeve-Transform (KLT) 기반의 Classified Vector Quantization (KLT-CVQ) 방식이 제안되었으며, 이는 KLT 기반의 Adaptive Entropy-Constrained Quantization (KLT-AECQ) 방식으로 확장되었다. 기존의 KLT-AECQ 에서는 지각적인 성능 향상을 위하여 formant weighting 필터를 사용한다. 본 논문에서는 이 필터 대신에 Spectral Amplitude Warping (SAW) 필터를 적용함으로써, KLT-AECQ 코더의 지각적인 성능을 향상하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.1845-1865
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• 2019

Current Internet is designed by lots of service providers with different objects and policies which make the direct deployment of radically new architecture and protocols on Internet nearly impossible without reaching a consensus among almost all of them. Network virtualization is proposed to fend off this ossification of Internet architecture and add diversity to the future Internet. As an important part of network virtualization, virtual network embedding (VNE) problem has received more and more attention. In order to solve the problems of large embedding cost, low acceptance ratio (AR) and environmental adaptability in VNE algorithms, cognitive method is introduced to improve the adaptability to the changing environment and a cognitive virtual network embedding algorithm based on weighted relative entropy (WRE-CVNE) is proposed in this paper. At first, the weighted relative entropy (WRE) method is proposed to select the suitable substrate nodes and paths in VNE. In WRE method, the ranking indicators and their weighting coefficients are selected to calculate the node importance and path importance. It is the basic of the WRE-CVNE. In virtual node embedding stage, the WRE method and breadth first search (BFS) algorithm are both used, and the node proximity is introduced into substrate node ranking to achieve the joint topology awareness. Finally, in virtual link embedding stage, the CPU resource balance degree, bandwidth resource balance degree and path hop counts are taken into account. The path importance is calculated based on the WRE method and the suitable substrate path is selected to reduce the resource fragmentation. Simulation results show that the proposed algorithm can significantly improve AR and the long-term average revenue to cost ratio (LTAR/CR) by adjusting the weighting coefficients in VNE stage according to the network environment. We also analyze the impact of weighting coefficient on the performance of the WRE-CVNE. In addition, the adaptability of the WRE-CVNE is researched in three different scenarios and the effectiveness and efficiency of the WRE-CVNE are demonstrated.

• The Korean Journal of Ecology
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• 제10권2호
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• pp.91-107
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• 1987

This study is concerned with some methods and applications, used as a basis on information and entropy analysis of vegetation data. These methods are adopted for the evaluating the effect of sampling intensity on information, which repersnets the departure of observed variable from standard component. Classes on the data matrix are caluculated by using marginal dispersion array for rank and weighting information program. Finally the information and entropy are computed by applying seven options. On the application of vegetation studies, two models for cluster analysis and analysis of concentration are explained in detail. Cluster analysis is based on use of equivocation information and Rajski's metrics. The analysis of concentration utilizes coherence coefficience being transformed values, which has been adjusted from blocks and entropy values. The relationship btween three begetation clusters and four stands of Naejangsan data is highly significant in 79% of total variance. Cluster A relatively tends to prefer north side, and cluster C south side.

• Asia pacific journal of information systems
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• 제16권1호
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• pp.85-101
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• 2006

Actual type of aggregation performed by an ordered weighted averaging (OWA) operator heavily depends upon the weighting vector. A number of approaches have been suggested for obtaining the associated weights. In this paper, we present analytic forms of OWA operator weighting functions, each of which has such properties as rank-based weights and constant value of orness, irrespective of number of objectives aggregated. Specifically, we propose four analytic forms of OWA weighting functions that can be positioned at 0.25, 0.334, 0.667, and 0.75 on the orness scale. The merits for using these weights over other weighting schemes can be mentioned in a couple of ways. Firstiy, we can efficiently utilize the analytic forms of weighting functions without solving complicated mathematical programs once the degree of orness is specified a priori by decision maker. Secondly, combined with well-known OWA operator weights such as max, min, and average, any weighting vectors, having a desired value of orness and being independent of the number of objectives, can be generated. This can be accomplished by convex combinations of predetermined weighting functions having constant values of orness. Finally, in terms of a measure of dispersion, newly generated weighting vectors show just a few discrepancies with weights generated by maximum entropy OWA.

• Journal of Ship and Ocean Technology
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• 제5권1호
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• pp.30-37
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• 2001

Ship optimal design is a multi-objective decision-making process and its optimal solution does not exit in general. It is a problem in which the decision-maker is very interested that an effective solution is how to be found which has good characteristic and is substituted for optimal solution in a sense. In the previous methods of multi-objective decision-making, the weighting coefficients are decided from the point of view of individuals which have a bit sub-jective an unilateral behavior. in order to fairly and objectively decide the weighting coeffi-cients, which are considered to be optimal in all system of multi-objective decision-making and satisfactory solution to the decision-maker, the pater presents a method of applying the Technology of the Biggest Entropy. It is proved that the method described in the paper is very feasible and effective be means of a practical example of ship optimal design.