• Title/Summary/Keyword: Optimal weights

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The comparative analysis of optimal designed web expanded beams via improved harmony search method

  • Erdal, Ferhat
    • Structural Engineering and Mechanics
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    • v.54 no.4
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    • pp.665-691
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    • 2015
  • This study aims at comparing the optimum design of two common types open web expanded beams: with hexagonal openings, also called castellated beams and beams with circular openings referred to as cellular beams. The minimum weights of both beams are taken as the objective functions while the design constraints are respectively implemented from The Steel Construction Institute Publication Numbers 5 and 100. The design methods adopted in these publications are consistent with BS5950 parts. The formulation of the design problem considering the limitations of the above mentioned turns out to be a discrete programming problem. Improved harmony search algorithm is suggested to compare the optimum design of mentioned web-expanded beams to analysis the performance of both beams. The design algorithms based on the technique select the optimum Universal Beam sections, dimensional properties of hexagonal and circular holes and total number of openings along the beam as design variables.

Distance Sensitive AdaBoost using Distance Weight Function

  • Lee, Won-Ju;Cheon, Min-Kyu;Hyun, Chang-Ho;Park, Mi-Gnon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.143-148
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    • 2012
  • This paper proposes a new method to improve performance of AdaBoost by using a distance weight function to increase the accuracy of its machine learning processes. The proposed distance weight algorithm improves classification in areas where the original binary classifier is weak. This paper derives the new algorithm's optimal solution, and it demonstrates how classifier accuracy can be improved using the proposed Distance Sensitive AdaBoost in a simulation experiment of pedestrian detection.

Density-Order Index Rule for Stock Location in a Distribution Warehouse

  • Hwang, Hark;Cha, Chun-Nam
    • Journal of Korean Institute of Industrial Engineers
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    • v.15 no.1
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    • pp.41-50
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    • 1989
  • This paper deals with the problem of space allocation of items within a warehouse. Recognizing the importance of weights associated with material handling, mathematical models are developed for two cases, out-and-back selection and storage retrieval interleaving. It is proved that the density order index rule we proposed generates an optimal solution for the first model. An example problem solved with the pairwise interchange method indicates that the rule is also fairly efficient for the second model. The proposed rule is compared with other assignment rules of warehouse space such as COI rule, space and popularity.

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A Component-wise Load Forecasting by Adaptable Artificial Neural Network (적응력을 갖는 신경회로망에 의한 성분별 부하 예측)

  • Lim, Jae-Yoon;Kim, Jin-Soo;Kim, Jung-Hoon
    • Proceedings of the KIEE Conference
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    • 1994.11a
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    • pp.21-23
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    • 1994
  • The degree of forecast accuracy with BP-algorithm largely depends upon the neuron number in hidden layer. In order to construct the optimal structure, first, we prescribe the error bounds of learning procedure, and then, we provid the method of incrementing the number of hidden neurons by using the derivative of errors with respect to an output neuron weights. For the case study, we apply the proposed method to forecast the component-wise residential load, and compare this results to that of time series forecasting.

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Customer Relationship Management in Telecom Market using an Optimized Case-based Reasoning (최적화 사례기반추론을 이용한 통신시장 고객관계관리)

  • An, Hyeon-Cheol;Kim, Gyeong-Jae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.285-288
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    • 2006
  • Most previous studies on improving the effectiveness of CBR have focused on the similarity function aspect or optimization of case features and their weights. However, according to some of the prior research, finding the optimal k parameter for the k-nearest neighbor (k-NN) is also crucial for improving the performance of the CBR system. Nonetheless, there have been few attempts to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors that combine, as well as the weight of each feature. The new model is applied to the real-world case of a major telecommunication company in Korea in order to build the prediction model for the customer profitability level. Experimental results show that our GA-optimized CBR approach outperforms other AI techniques for this mulriclass classification problem.

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Collaborative Filtering Algorithm Based on User-Item Attribute Preference

  • Ji, JiaQi;Chung, Yeongjee
    • Journal of information and communication convergence engineering
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    • v.17 no.2
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    • pp.135-141
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    • 2019
  • Collaborative filtering algorithms often encounter data sparsity issues. To overcome this issue, auxiliary information of relevant items is analyzed and an item attribute matrix is derived. In this study, we combine the user-item attribute preference with the traditional similarity calculation method to develop an improved similarity calculation approach and use weights to control the importance of these two elements. A collaborative filtering algorithm based on user-item attribute preference is proposed. The experimental results show that the performance of the recommender system is the most optimal when the weight of traditional similarity is equal to that of user-item attribute preference similarity. Although the rating-matrix is sparse, better recommendation results can be obtained by adding a suitable proportion of user-item attribute preference similarity. Moreover, the mean absolute error of the proposed approach is less than that of two traditional collaborative filtering algorithms.

Vertical Handoff Decision Algorithm combined Improved Entropy Weighting with GRA for Heterogeneous Wireless Networks

  • Zhao, Shasha;Wang, Fei;Ning, Yueqiang;Xiao, Yi;Zhang, Dengying
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.11
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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.

A Study on the Method of Non-Standard Cargo Volume Calculation Based on LiDar Sensor for Cargo Loading Optimization (화물 선적 최적화를 위한 LiDar 센서 기반 비규격 화물 체적산출 방법 연구)

  • Jeon, Young Joon;Kim, Ye Seul;Ahn, Sun Kyu;Jeong, Seok Chan
    • Journal of Korea Multimedia Society
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    • v.25 no.4
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    • pp.559-567
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    • 2022
  • The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

Task Scheduling and Resource Management Strategy for Edge Cloud Computing Using Improved Genetic Algorithm

  • Xiuye Yin;Liyong Chen
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.450-464
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    • 2023
  • To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

Contribution analysis of Hanwoo carcass traits on unit price in national slaughter house

  • Eum, Seung-Hoon;Park, Hu-Rak;Seo, Jakyeom;Cho, Seong-Keun;Kim, Byeong-Woo
    • Korean Journal of Agricultural Science
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    • v.43 no.4
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    • pp.603-611
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    • 2016
  • The aim of this study was to analyze the contribution factors (backfat thickness, eye muscle area, carcass weight, marbling score, and feeding period) affecting meat unit price (South-Korean Won / Kg of meat). The best slaughtering age to maximize unit price was also assumed. All data used in this study were acquired from the Korea Institute for Animal Products Quality Evaluation from 2010 to 2014. Contributions to the estimated unit price of cows by the following factors, backfat thickness, eye muscle area, carcass weights, feeding period, and marbling score were 2.65%, 0.04%, 1.58%, 1.58%, and 95.72%, respectively. Contribution to estimated unit price of steers by the same factors (backfat thickness, eye muscle area, carcass weights, feeding period, and marbling score) were 7.88%, 1.24%, 0.07%, 90.81%, and 95.72%, respectively. Slaughtering ages ranged from 26 to 36 months and the data were separated into each month for an 11 month period. The unit price of meat from Hanwoo slaughtered at 30 months was highest among groups. The lowest unit price was observed in the group belonging to the Hanwoo slaughtered at 36 months. In conclusion, of all contributing factors, marbling score affected unit price the most. Based on our results, it is recommended that the optimal slaughtering age be set at 30 months to maximize unit price. Moreover, the feeding of beef cattle past 30 months of age is not recommended because of the increase in feeding costs.