• Title/Summary/Keyword: 계곡

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Acceleration of Learning speed Neural Networks by Reducing Weight Oscillations (가중치 진동의 감소를 이용한 신경회로망의 학습속도 향상)

  • 임빈철;박동조
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.10a
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    • pp.251-254
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    • 1998
  • 본 논문에서는 신경회로망의 수렴속도를 높이기 위한 알고리즘을 제안한다. 전형적인 역전파 학습방식은 느린 수렴속도가 단점으로 제기되는데 이는 비용함수의 계곡부근에서 가중치의 궤적이 심한 진동현상을 보이기 때문이다. 이 문제를 해결하기 위해서 본 논문에서는 경사법에서 사용되는 갱신방향을 계곡의 진행방향을 이용하여 변경한다. 모의실험을 통하여 제안된 방법으로 가중치의 궤적에 나타나는 진동을 줄이고 수렴속도를 향상시킬 수 있음을 보인다.

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Observation of the Cold-air Drainage and Thermal Belt Formation in a Small Mountainous Watershed by Using an Infrared Imaging Radiometer (적외선 영상 복사계를 이용한 산간집수역의 찬공기 배수와 온난대 형성 관측)

  • Yun, Jin-I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.13 no.2
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    • pp.79-86
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    • 2011
  • Cold-air drainage and pooling occur in most mountain valleys at night. Local climates with cold-air pooling could affect phenology and distribution of crop plants. A high resolution infrared imaging radiometer was used to visualize the cold-air drainage and thermal belt formation over a small mountainous watershed (ca. $10{\times}5{\times}1$ km for the maximum length${\times}$width${\times}$depth). Thermal images on $640{\times}480$ pixels were scanned across the Akyang valley (south of Mt. Jiri National Park) by the radiometer installed at a local peak ('Hyongjebong', 1,117 m a.s.l.) at dawn of 17 May 2011, when the synoptic condition was favorable for the surface cooling and cold-air drainage. Major findings are: (1) Cold-air drainage and accumulation was clearly identified by the lowest brightness temperature mainly at the valley bottom. (2) So-called 'thermal belt' with higher brightness temperature was found partway up the valley sidewalls and showed up to $5^{\circ}C$ departure from the valley bottom temperature. (3) Digital thermography showed feasibility for validation of the high definition geospatial temperature models currently in use for the plot-specific agrometeorological service.

Unrecorded Liverwort species from Korean flora (한반도 미기록 태류식물)

  • Choi, Seung Se;Bakalin, Vadim A.;Kim, Chul-Hwan;Sun, Byung-Yun
    • Korean Journal of Plant Taxonomy
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    • v.42 no.1
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    • pp.80-90
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    • 2012
  • While preparing a floristic study of Korean hepatics, we discovered the following 10 unrecorded species from Mt. Jiri-san (maximum height, 1,915 m) and Mt. Seorak-san (maximum height, 1,708 m): Neotrichocolea bissetii (Mitt.) S. Hatt., Calypogeia angusta Steph., Cephaloziella massalongii K. Mller, Harpanthus scutatus (F. Weber & D. Mohr) Spruce, Plectocolea torticalyx (Steph.) S. Hatt., Anastrophyllum michauxii (F. Weber) H. Buch, Lophozia excisa (Dicks.) Dumort., Lophozia lantratoviae Bakalin, Mylia verrucosa Lindb., Scapania sphaerifera H. Buch. They are distributed near streams and/or on the top of a ridge on Mt. Jiri-san and Mt. Seorak-san.

Vegetation Structure of Secheon Valley Area and Forest Vegetation Types in Mt. Sikjang (식장산 산림식생유형과 세천계곡부의 식생구조)

  • Hwang, Seon-Mi;Yun, Chung-Weon
    • Korean Journal of Environmental Biology
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    • v.25 no.3
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    • pp.249-259
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    • 2007
  • This study was carried out the analysis of forest vegetation structure using the phytosociological methods by Braun-Blanquet from April to November in 2006. The results were summarized as follows. The forest vegetation was classified into 23 communities and 3 forest ecosystem types such as slope forest type, valley forest type and artificial forest type. By the actual vegetation map, Quercus mongolica forest was widely distributed in the area and Pinus densiflora forest and Quercus variabilis forest in the southern parts of the slope and valley forest mainly in valley area, respectively. The importance value in the Q. mongolica forest and artificial forest was absolutely high for the species dominated in tree layer. The typical valley species of Lindera erythrocarpa and Styrax japonica were abundantly occupied in the all layers. Species diversity indices of Alnus hirsta forest was the lowest as 0.2191, and that of valley forest was about 0.9, the highest among the all forest types.