• Title/Summary/Keyword: generalization

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A Study on the Effective Algorithms for tine Generalization (선형성 지형자료의 일반화에 대한 효율적인 알고리즘에 관한 연구)

  • 김감래;이호남
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.12 no.1
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    • pp.43-52
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    • 1994
  • This paper outlines a new approach to the line generalization when preparing small scale map on the basis of existing large scale digital map. Line generalizations are conducted based on Douglas algorithm using 1/25,000 scale topographic maps of southeastern JEJU island which produced by National Geographic Institute to analyze the fitness to the original and problems of graphical representation. Compare to the same scale map which was generated by manual method, a verity of small, but sometimes significant errors & modification of topological relationship have been detected. The research gives full details of three algorithms that operationalize the smallest visible object method, together with some empirical results. A comparison of the results produced by the new algorithms with those produced by manual generalization and Douglas method of data reduction is provided. Also this paper presents the preliminary results of an relationships between the size of smallest visual object and requiring data storages for each algorithms.

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Modified Error Back Propagation Algorithm using the Approximating of the Hidden Nodes in Multi-Layer Perceptron (다층퍼셉트론의 은닉노드 근사화를 이용한 개선된 오류역전파 학습)

  • Kwak, Young-Tae;Lee, young-Gik;Kwon, Oh-Seok
    • Journal of KIISE:Software and Applications
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    • v.28 no.9
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    • pp.603-611
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    • 2001
  • This paper proposes a novel fast layer-by-layer algorithm that has better generalization capability. In the proposed algorithm, the weights of the hidden layer are updated by the target vector of the hidden layer obtained by least squares method. The proposed algorithm improves the learning speed that can occur due to the small magnitude of the gradient vector in the hidden layer. This algorithm was tested in a handwritten digits recognition problem. The learning speed of the proposed algorithm was faster than those of error back propagation algorithm and modified error function algorithm, and similar to those of Ooyen's method and layer-by-layer algorithm. Moreover, the simulation results showed that the proposed algorithm had the best generalization capability among them regardless of the number of hidden nodes. The proposed algorithm has the advantages of the learning speed of layer-by-layer algorithm and the generalization capability of error back propagation algorithm and modified error function algorithm.

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The Study on Simplification in Digital Map Generalization (수치지도 일반화에 있어서 단순화에 관한 연구)

  • 최병길
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.2
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    • pp.199-208
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    • 2001
  • The digital map in Korea has been producted and utilized independently according to scales such as 1:1,000, 1:5,000, and 1:25,000. Therefore, whenever we need to obtain the spatial data of other scales, we have to product the digital maps over and over again which it is time-consuming and ineconomic. To solve these problems, it has been accomplished many researches on map generalization to make digital maps in small scale from the master data of large scale. This paper aims to analyze the conversion characteristics of the large scale to the small scale by simplification of map generalization. For this purpose, it is proposed the algorithm for the simplification process of digital map and it is investigated the simplification characteristic of digital map through the experiment on the conversion of 1:5,000 scale into 1:25.000 scale. The results show that Area-Preservation algorithm indicates the good agreement with the original data in terms of the area and features of building layer compared to Douglas-Peucker algorithm and Reumann-Witkam algorithm.

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Learning Domain Invariant Representation via Self-Rugularization (자기 정규화를 통한 도메인 불변 특징 학습)

  • Hyun, Jaeguk;Lee, ChanYong;Kim, Hoseong;Yoo, Hyunjung;Koh, Eunjin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.24 no.4
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    • pp.382-391
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    • 2021
  • Unsupervised domain adaptation often gives impressive solutions to handle domain shift of data. Most of current approaches assume that unlabeled target data to train is abundant. This assumption is not always true in practices. To tackle this issue, we propose a general solution to solve the domain gap minimization problem without any target data. Our method consists of two regularization steps. The first step is a pixel regularization by arbitrary style transfer. Recently, some methods bring style transfer algorithms to domain adaptation and domain generalization process. They use style transfer algorithms to remove texture bias in source domain data. We also use style transfer algorithms for removing texture bias, but our method depends on neither domain adaptation nor domain generalization paradigm. The second regularization step is a feature regularization by feature alignment. Adding a feature alignment loss term to the model loss, the model learns domain invariant representation more efficiently. We evaluate our regularization methods from several experiments both on small dataset and large dataset. From the experiments, we show that our model can learn domain invariant representation as much as unsupervised domain adaptation methods.

Developing a Neural-Based Credit Evaluation System with Noisy Data (불량 데이타를 포함한 신경망 신용 평가 시스템의 개발)

  • Kim, Jeong-Won;Choi, Jong-Uk;Choi, Hong-Yun;Chuong, Yoon
    • The Transactions of the Korea Information Processing Society
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    • v.1 no.2
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    • pp.225-236
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    • 1994
  • Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set[2]. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

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The Selection Methodology of Road Network Data for Generalization of Digital Topographic Map (수치지형도 일반화를 위한 도로 네트워크 데이터의 선택 기법 연구)

  • Park, Woo Jin;Lee, Young Min;Yu, Ki Yun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.3
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    • pp.229-238
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    • 2013
  • Development of methodologies to generate the small scale map from the large scale map using map generalization has huge importance in management of the digital topographic map, such as producing and updating maps. In this study, the selection methodology of map generalization for the road network data in digital topographic map is investigated and evaluated. The existing maps with 1:5,000 and 1:25,000 scales are compared and the criteria for selection of the road network data, which are the number of objects and the relative importance of road network, are analyzed by using the T$\ddot{o}$pfer's radical law and Logit model. The selection model derived from the analysis result is applied to the test data, and the road network data of 1:18,000 and 1:72,000 scales from the digital topographic map of 1:5,000 scale are generated. The generalized results showed that the road objects with relatively high importance are selected appropriately according to the target scale levels after the qualitative and quantitative evaluations.

Linguistic Description and Theory

  • Nakajima, Heizo
    • Korean Journal of English Language and Linguistics
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    • v.1 no.3
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    • pp.349-368
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    • 2001
  • We have brought up several distinct types of English clausal constructions, and have been lead to the descriptive generalization in (14),repeated here as (33): (33) Reduced clauses cannot occur in non-complement positions. The generalization in (33) refers to two theory-internal notions, reduced clauses and non-complement positions. Both notions are concerned with the composition of syntactic structures to be defined by X-bar theory. Without these theoretical notions, it would be difficult to describe in a general form the fact that certain types of complement clauses-namely, null-that clauses, if-clauses, Acc-ing gerund, ECM complement clauses, and Raising complement clauses-cannot occur in particular syntactic positions. Instead, one would have to describe this fact for each clause type, in such a way that null-that clauses cannot occur in such and such positions, and if-clauses cannot occur in such and such positions, and Acc-ing gerund cannot occur in such and such positions, and so on, although the positions in which they cannot occur are totally the same. Given the terminology of X-bar theory, however, it has turned out that these types of complement clauses are all reduced clauses, and the positions where they cannot occur are all non-complement positions. Then, the generalization has obtained that reduced clauses cannot occur in non-complement positions. It is a theoretical issue, and differs depending upon theories, how to explain why such a descriptive generalization holds at all. Hopefully, the demonstration here provides a piece of evidence showing that a theory or a particular theoretical nation plays an important role in the description of linguistic facts. Moreover, I have made a crucial prediction on the basis of the well-accepted theoretical assumption the ECM complement clauses and Raising complement clauses are reduced clauses; namely, the prediction that these types of clauses cannot occur in non-complement position. The prediction based upon the theoretical assumption is actually borne out, as illustrated earlier. The illustration of the prediction, I hope, shows that a theory or a particular theoretical assumption, coupled with another theoretical assumption, allows us to make some interesting predictions. Predictions serve to widen a range of linguistic facts to be described. A theory plays a crucial part in finding out interesting facts as well as in describing them in some general forms. Finally, let me state a few words as to the recent generative theory in connection with linguistic description. The recent generative theory is getting more and more abstract. I think it is moving toward a good direction as cognitive science. It will contribute, among others, to the inquiry into what is knowledge that is very specific to language faculty, and into how it interacts with other cognitive faculties. However, I am suspicious about how much the abstract generative theory will contribute to the description of linguistic facts in a particular language. While generative theory is claimed to aim both for descriptive adequacy and for explanatory adequacy, the recent generative theory is likely to put much more weight on explanatory adequacy. In my view, a less abstract theory is enough, or even more useful, for the purpose of linguistic description. Of course, how abstract theory one should adopt as a framework differs depending upon what aspect of language one attempts to describe. What I would like to emphasize here is that linguistic theory does not conflicts with linguistic description, and a linguistic theory with an appropriate degree of abstractness serves as a tool for finding out new interesting facts, as well as for describing them in some general, elegant forms.

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Location Generalization Method of Moving Object using $R^*$-Tree and Grid ($R^*$-Tree와 Grid를 이용한 이동 객체의 위치 일반화 기법)

  • Ko, Hyun;Kim, Kwang-Jong;Lee, Yon-Sik
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.2 s.46
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    • pp.231-242
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    • 2007
  • The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

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The Positional Accuracy Quality Assessment of Digital Map Generalization (수치지도 일반화 위치정확도 품질평가)

  • 박경식;임인섭;최석근
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.2
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    • pp.173-181
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    • 2001
  • It is very important to assess spatial data quality of a digital map produced through digital map generalization. In this study, as a aspect of spatial data quality maintenance, we examined the tolerate range of theoretical expectation accuracy and established the quality assessment standard in spatial data for the transformed digital map data do not act contrary to the digital map specifications and the digital map accuracy of the relational scale. And, transforming large scale digital map to small scale, if we reduce complexity through processes as simplification, smoothing, refinement and so on., the spatial position change may be always happened. thus, because it is very difficult to analyse the spatial accuracy of the transformed position, we used the buffering as assessment method of spatial accuracy in digital map generalization procedure. Although the tolerated range of generic positioning error for l/l, 000 and l/5, 000 scale is determined based on related law, because the algorithms adapted to each processing elements have different property each other, if we don't determine the suitable parameter and tolerance, we will not satisfy the result after generalization procedure with tolerated range of positioning error. The results of this study test which is about the parameters of each algorithm based on tolerated range showed that the parameter of the simplification algorithm and the positional accuracy are 0.2617 m, 0.4617 m respectively.

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Improving Health-related Behaviors and General Self-control Behaviors through a College-level Self-management Course (자기관리수업을 통한 충동성의 감소가 건강증진 행동 및 전반적인 다양한 자기통제 행동에 미치는 영향)

  • Seo, Jihyeon;Chung, Kyong-Mee
    • Korean Journal of Health Psychology
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    • v.19 no.4
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    • pp.929-955
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    • 2014
  • The purpose of this study was to 1) explore the effectiveness of a college-level self-management (SM) course in improving a target behavior and reducing impulsivity, 2) investigate improvements in other non-target self-control behaviors(generalization of self-control), and 3) determine whether change in impulsivity could predict the generalization of self-control. A total of 128 College students who took the SM course were included. Participants completed the computerized delay-discounting task, self-report impulsiveness scale, and general self-control behavior questionnaire at the beginning and end of the course. After participants had defined their target behaviors, they self-monitored and recorded their behaviors everyday throughout the course. Results revealed that 63% of the participants successfully changed their target behaviors after the course. Although differing depending on the type of target behavior, thoes who successfully changed their target behaviors reported decreases in impulsivity and increases in other self-control behaviors such as physical exercise, healthy diet, study habits, and time management, after the course. Furthermore, the decrease of impulsivity significantly predicted the generalization of self-control in the exercise and diet groups. The results indicate that reduced impulsivity is related to improvements in a target behavior and general self-control behaviors in other spheres. Implications and limitations are also discussed.