Research on Combined Weight of Target Threat Index of Information Fusion

2014 ◽  
Vol 599-601 ◽  
pp. 1629-1635
Author(s):  
Ke Hu Xu ◽  
Jin Yu Chen ◽  
De Peng Kong
Keyword(s):  
Information Fusion ◽  
Weight Vector ◽  
Vector Model ◽  
Weight Optimization ◽  
Threat Index ◽  
Minimal Deviation ◽  
The Right ◽  
Index Weight ◽  
Optimal Weight Vector ◽  
Deviation Method

To the characteristics of index weight, using minimal deviation method as the theoretical tools to create index portfolio weight optimization model. Using genetic algorithms to solve the optimal weight vector model which has the capability of global searching . Through example demonstrate, the right combination to get the weight vector of the model is more reasonable and scientific, and genetic algorithm process a simpler and easier way to understand than traditional methods.

scholarly journals Retrieving Model for Design Patterns

1970 ◽  
Vol 3 (1) ◽  
pp. 51-55
Author(s):  
Sarun Intakosum ◽  
Weenawadee Muangon
Keyword(s):  
Design Patterns ◽  
Vector Space Model ◽  
Weight Vector ◽  
Problem Domain ◽  
Design Problems ◽  
Space Model ◽  
Proposed Model ◽  
The Right ◽  
Index Weight ◽  
Correct Design

The purpose of this research is to develop a retrieving model for design patterns, based on problem domain context. The research aims to provide a convenient way for developers to access to the right design patterns that can solve their design problems. The proposed model is composed of two major parts, the analysis of design pattern documents to create searchindexes, and the calculation of index weight. Vector space model is used to calculate similarity between queries and documents. The result of this research shows that precision of the proposed model, in retrieving correct design patterns, is about 70 percents in average.

A complementary webometric ranking system based on the website quality and traffic measures: A study focusing on top-ranked world universities

2021 ◽  
pp. 1-18
Author(s):  
Sajjad Farashi ◽  
Saeed Bashirian
Keyword(s):  
Weight Vector ◽  
Quality Factors ◽  
Ranking System ◽  
Web Based ◽  
Website Quality ◽  
Scientific Advancement ◽  
Standard Models ◽  
Algorithm Framework ◽  
Scientific Results ◽  
Optimal Weight Vector

Ranking of universities regarding their web-based activities plays a pivotal role in promoting scientific advancement since it motivates the open access accessibility to scientific results. In this study, a new ranking system based on the website quality factors and traffic evaluation was proposed. Since top-ranked universities are usually considered as the standard models for lower ranked ones, the focus of this study was on top-ranked universities. The proposed ranking was compared with well-known Webometrics ranking system. The website traffic and quality assessment were acquired for websites of top-ranked world universities and the correlation between these indices and the Webometrics ranking was evaluated. The summation of the weighted value of obtained measures according to an optimal weight vector obtained by a genetic algorithm framework was used for ranking purposes. The results showed that the website total traffic size was correlated with Webometrics rank (R≈-0.6, p< 0.01). Also, using the weighted value of website quality and traffic measures, the proposed ranking system could predict Webometrics ranking by the accuracy of up to 69%. Even though the method was proposed for universities, it could be applied for ranking other types of centers or companies, provided that the suitable cost function for the genetics algorithm framework was defined.

scholarly journals Algorithm for Probabilistic Dual Hesitant Fuzzy Multi-Criteria Decision-Making Based on Aggregation Operators With New Distance Measures

Mathematics ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 280 ◽  
Author(s):  
Harish Garg ◽  
Gagandeep Kaur
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
Weight Vector ◽  
Aggregation Operators ◽  
Distance Measures ◽  
Weighted Averaging ◽  
Hesitant Fuzzy Set ◽  
Maximum Deviation ◽  
Dual Hesitant Fuzzy Set ◽  
Deviation Method

Probabilistic dual hesitant fuzzy set (PDHFS) is an enhanced version of a dual hesitant fuzzy set (DHFS) in which each membership and non-membership hesitant value is considered along with its occurrence probability. These assigned probabilities give more details about the level of agreeness or disagreeness. By emphasizing the advantages of the PDHFS and the aggregation operators, in this manuscript, we have proposed several weighted and ordered weighted averaging and geometric aggregation operators by using Einstein norm operations, where the preferences related to each object is taken in terms of probabilistic dual hesitant fuzzy elements. Several desirable properties and relations are also investigated in details. Also, we have proposed two distance measures and its based maximum deviation method to compute the weight vector of the different criteria. Finally, a multi-criteria group decision-making approach is constructed based on proposed operators and the presented algorithm is explained with the help of the numerical example. The reliability of the presented decision-making method is explored with the help of testing criteria and by comparing the results of the example with several prevailing studies.

scholarly journals IMAGE RESTORATION METHOD, INVARIANT TO SIGNAL CORRELATION IN THE INFORMATION SYSTEM WITH ADAPTIVE ANTENNA ARRAY

2020 ◽  
pp. 64-76
Author(s):  
V.V. Skachkov ◽  
Keyword(s):  
Information System ◽  
Image Restoration ◽  
Antenna Array ◽  
Correlation Matrix ◽  
Signal To Noise Ratio ◽  
Weight Vector ◽  
Adaptive Antenna ◽  
Adaptive Antenna Array ◽  
Optimal Weight ◽  
Optimal Weight Vector

The problem of image signal processing in the information system with adaptive antenna array based on the inversion of sample estimates of correlation matrix of observations is considered. The example of the maximum signal-to-noise ratio criterion shows the problem, inherent in classical methods of finding the optimal weight vector under a priori uncertainty conditions when detecting correlated image signals. It has been concluded that the dependence of these methods on the inverse of estimation of the correlation matrix of observations leads to the impossibility of separating correlated image signals. As a consequence, the use of classical methods of finding the optimal weight vector in the information system with adaptive antenna array is effective only in the case of image restoration from a single signal source, with the signal received on the set of independent jamming background. A novel method, invariant to the correlation of image signals, has been developed for finding the optimal weight vector without the usage of correlation matrix of observations. An image restoration algorithm invariant to correlation of image signals in the information system with adaptive antenna array is proposed. Statistical models have been constructed for the classical method based on the criterion of maximum signal-to-noise ratio and invariant to correlation method of image restoration in following cases: a single source against the jamming background of two independent sources; two independent sources against the jamming background. Simulation results in the information system with adaptive antenna array are presented, showing to visually assess efficiency of proposed methods of image signal restoration using optimal weight vector. Detailed analysis of the results obtained is carried out.

scholarly journals A New Method for Active Cancellation of Engine Order Noise in a Passenger Car

2018 ◽  
Vol 8 (8) ◽  
pp. 1394 ◽  
Author(s):  
Sang-Kwon Lee ◽  
Seungmin Lee ◽  
Jiseon Back ◽  
Taejin Shin
Keyword(s):  
Active Control ◽  
Adaptive Filter ◽  
Weight Vector ◽  
Noise Signal ◽  
Interior Noise ◽  
Frequency Variation ◽  
Engine Noise ◽  
Optimal Weight ◽  
Engine Order ◽  
Optimal Weight Vector

This paper presents a novel active noise cancellation (ANC) method to reduce the engine noise inside the cabin of a car. During the last three decades, many methods have been developed for the active control of a quasi-stationary narrowband sinusoidal signal. However, since the interior noise signal is non-stationary with a fast frequency variation when the car accelerates rapidly, these methods cannot stably reduce the interior noise. The proposed method can reduce the interior noise stably even if the speed of the car is changed quickly. The method uses an adaptive filter with an optimal weight vector for the active control of such an engine noise. The method of determining the optimal weight vector of an adaptive filter is demonstrated. In order to validate the advantages of the proposed method, a conventional method and the proposed method are simulated with three synthesized signals. Finally, the proposed method is applied to the cancellation of booming noise in a sport utility vehicle. We demonstrate that the performance of the ANC system with the proposed algorithm is excellent for the attenuation of engine noise inside the cabin of a car.

scholarly journals Mitigation of narrowband stationary interference in the telemetry complex based on an autocompensator with remote channels.

2020 ◽  
Vol 2020 (12) ◽  
Author(s):  
V.Yu. Semenov ◽  
◽  
A.V. Korotyshev ◽  
◽  
Keyword(s):  
Numerical Simulation ◽  
Computational Complexity ◽  
Analytical Solution ◽  
High Power ◽  
Correlation Matrix ◽  
Weight Vector ◽  
Optimal Weight ◽  
Direct Inversion ◽  
Optimal Weight Vector ◽  
Standard Arrangement

The problem of combating stationary interference in the areas of operation of ground-based telemetry systems is considered. One of the most annoying types of interference is high-power narrowband TV interference. They are emitted from television towers and their position is known in advance. A solution to this problem is proposed by using a multichannel auto-compensator with a non-standard arrangement of compensation channels. An analytical solution is obtained for the optimal weight vector of the auto-compensator of interference, based on the method of power vectors. This method does not require direct inversion of the interference correlation matrix. The computational complexity of the proposed method is estimated and it is shown that it has a much lower computational complexity compared to the method of direct inversion of the interference correlation matrix. The results of numerical simulation of the interference suppression coefficient are presented. Its effectiveness has been shown.

Research on Improved AHP Evaluation in Supporting the Right to Determine the Weight of Deep Foundation

2014 ◽  
Vol 919-921 ◽  
pp. 731-734
Author(s):  
Hong Yan Jiang ◽  
Gang Gang Yu
Keyword(s):  
Scaling Theory ◽  
Deep Foundation ◽  
Foundation Pit ◽  
Deep Foundation Pit ◽  
Judgment Matrix ◽  
The Right ◽  
Index Weight ◽  
Selection Of

The traditional AHP in the judgment matrix is established by using 1-9 scale, this scale has transfer difference, consistency of judgment matrix and thinking is not equivalent shortcomings. The improved AHP scaling theory is used in deep foundation pit support index weight determination, the selection of foundation pit supporting is more comprehensive scientific reasonable accurate.

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