• 제목/요약/키워드: mapping algorithms

검색결과 365건 처리시간 0.031초

ACCELERATED HYBRID ALGORITHMS FOR NONEXPANSIVE MAPPINGS IN HILBERT SPACES

  • Baiya, Suparat;Ungchittrakool, Kasamsuk
    • Nonlinear Functional Analysis and Applications
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    • 제27권3호
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    • pp.553-568
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    • 2022
  • In this paper, we introduce and study two different iterative hybrid projection algorithms for solving a fixed point problem of nonexpansive mappings. The first algorithm is generated by the combination of the inertial method and the hybrid projection method. On the other hand, the second algorithm is constructed by the convex combination of three updated vectors and the hybrid projection method. The strong convergence of the two proposed algorithms are proved under very mild assumptions on the scalar control. For illustrating the advantages of these two newly invented algorithms, we created some numerical results to compare various numerical performances of our algorithms with the algorithm proposed by Dong and Lu [11].

최적 경로 알고리즘들의 계산비용 비교 및 트랜스포터의 최적 블록 운송 계획 적용 (Comparison of Optimal Path Algorithms and Implementation of Block Transporter Planning System)

  • 문종헌;유원선;차주환
    • 대한조선학회논문집
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    • 제53권2호
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    • pp.115-126
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    • 2016
  • In the process of ship building, it is known that the maintenance of working period and saving cost are one of the important part during the logistics of blocks transportation. Precise operational planning inside the shipyard plays a big role for a smooth transportation of blocks. But many problems arise in the process of block transportation such as the inevitable road damage during the transportation of the blocks, unpredictable stockyard utilization of the road associated with a particular lot number, addition of unplanned blocks. Therefore, operational plan needs to be re-established frequently in real time for an efficient block management. In order to find the shortest path between lot numbers, there are several representative methods such as Floyd algorithm that has the characteristics of many-to-many mapping, Dijkstra algorithm that has the characteristic of one-to-many mapping, and the A* algorithm which has the one-to-one mapping, but many authors have published without the mutual comparisons of these algorithms. In this study, some appropriate comparison have been reviewed about the advantages and disadvantages of these algorithms in terms of precision and cost analysis of calculating the paths and planning system to operate the transporters. The flexible operating plan is proposed to handle a situation such as damaged path, changing process during block transportation. In addition, an operational algorithm of a vacant transporter is proposed to cover the shortest path in a minimum time considering the situation of transporter rotation for practical use.

라돈 농도 분포도 작성을 위한 단변량 크리깅 기법의 정량적 비교 (Quantitative Comparison of Univariate Kriging Algorithms for Radon Concentration Mapping)

  • 곽근호;김용재;장병욱;박노욱
    • 한국지리정보학회지
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    • 제20권1호
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    • pp.71-84
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    • 2017
  • 토양, 암석, 지하수로부터 실내에 유입되는 라돈은 인간에게 큰 위해를 끼치는 방사능 가스이다. 라돈 가스의 위해성을 확인하기 위해 실내 라돈 농도를 측정해 오고 있는데, 추가적인 분석 수행을 위해서는 신뢰성 높은 분포도 작성이 매우 중요하다. 본 연구에서는 비대칭 분포를 나타내는 라돈 농도의 공간 분포도 작성을 위해 단변량 크리깅 기법들의 비교를 목적으로 정규 크리깅, 비선형 자료 변환 기반의 로그 정규 크리깅, 다중 가우시안 크리깅과 지시자 크리깅의 예측 능력을 비교하였다. 예측 능력을 비교 분석하기 위해 잭나이프 방법을 이용하여 검증을 수행하였으며, 자료 구간별 오차와 샘플링 밀도의 차이에 따른 오차도 추가적으로 분석하였다. 남한 지역을 대상으로 한 사례 연구 결과에서 전반적으로 정규 크리깅에 비해 비선형 자료 변환 기반 크리깅 기법들이 좋은 예측 능력을 보였으며, 비선형 자료 변환 기반 크리깅은 로그 정규 크리깅, 다중 가우시안 크리깅 순으로 좋게 나타났다. 그러나 공간 패턴과 높은 값의 재생산을 고려할 때, 높은 값의 예측 능력은 정규 크리깅이 가장 우수하였다. 본 연구의 결과는 비대칭 분포 자료의 공간 예측을 위한 크리깅 기법의 선정에 유용하게 사용될 것으로 기대된다.

A PERTURBED ALGORITHM OF GENERALIZED QUASIVARIATIONAL INCLUSIONS FOR FUZZY MAPPINGS

  • Jeong, Jae-Ug
    • East Asian mathematical journal
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    • 제17권1호
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    • pp.57-70
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    • 2001
  • In this paper, we introduce a class of generalized quasivariational inclusions for fuzzy mappings and show its equivalence with a class of fixed point problems. Using this equivalence, we develop the Mann and Ishikawa type perturbed iterative algorithms for this class of generalized quasivariational inclusions. Further, we prove the existence of solutions for the class of generalized quasivariational inclusions and discuss the convergence criteria for the perturbed algorithms.

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A NEW CLASS OF RANDOM COMPLETELY GENERALIZED STRONGLY NONLINEAR QUASI-COMPLEMENTARITY PROBLEMS FOR RANDOM FUZZY MAPPINGS

  • Huang, Nam-Jing
    • Journal of applied mathematics & informatics
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    • 제5권2호
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    • pp.357-372
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    • 1998
  • In this paper we introduce and study a new class of random completely generalized strongly nonlinear quasi -comple- mentarity problems with non-compact valued random fuzzy map-pings and construct some new iterative algorithms for this kind of random fuzzy quasi-complementarity problems. We also prove the existence of random solutions for this class of random fuzzy quasi-complementarity problems and the convergence of random iterative sequences generated by the algorithms.

Random completley generalized nonlinear variational inclusions with non-compact valued random mappings

  • Huang, Nan-Jing;Xiang Long;Cho, Yeol-Je
    • 대한수학회보
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    • 제34권4호
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    • pp.603-615
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    • 1997
  • In this paper, we introduce and study a new class of random completely generalized nonlinear variational inclusions with non-compact valued random mappings and construct some new iterative algorithms. We prove the existence of random solutions for this class of random variational inclusions and the convergence of random iterative sequences generated by the algorithms.

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Unveiling the mysteries of flood risk: A machine learning approach to understanding flood-influencing factors for accurate mapping

  • Roya Narimani;Shabbir Ahmed Osmani;Seunghyun Hwang;Changhyun Jun
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2023년도 학술발표회
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    • pp.164-164
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    • 2023
  • This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

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Integration of ERS-2 SAR and IRS-1 D LISS-III Image Data for Improved Coastal Wetland Mapping of southern India

  • Shanmugam, P.;Ahn, Yu-Hwan;Sanjeevi, S.;Manjunath, A.S.
    • 대한원격탐사학회지
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    • 제19권5호
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    • pp.351-361
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    • 2003
  • As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.

Low-complexity de-mapping algorithms for 64-APSK signals

  • Bao, Junwei;Xu, Dazhuan;Zhang, Xiaofei;Luo, Hao
    • ETRI Journal
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    • 제41권3호
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    • pp.308-315
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    • 2019
  • Due to its high spectrum efficiency, 64-amplitude phase-shift keying (64-APSK) is one of the primary technologies used in deep space communications and digital video broadcasting through satellite-second generation. However, 64-APSK suffers from considerable computational complexity because of the de-mapping method that it employs. In this study, a low-complexity de-mapping method for (4 + 12 + 20 + 28) 64-APSK is proposed in which we take full advantage of the symmetric characteristics of each symbol mapping. Moreover, we map the detected symbol to the first quadrant and then divide the region in this first quadrant into several partitions to simplify the formula. Theoretical analysis shows that the proposed method requires no operation of exponents and logarithms and involves only multiplication, addition, subtraction, and judgment. Simulation results validate that the time consumption is dramatically decreased with limited degradation of bit error rate performance.