볼록총채벌레는 제주도 감귤에서 경미한 피해만 보고되다가 2007년부터 다발생하여 그 피해가 갈수록 심각해지고 있다. 본 연구는 적산온도를 이용하여 볼록총채벌레 각 발생세대의 발생최성기를 예측할 수 있는 모형을 개발하고자 수행하였다. 볼록총채벌레 성충 발생세대수를 독립변수(x)로 취급하고 세대별 발생최성기의 적산온도를 종속변수(y)로 취급하여 직선 회귀식을 추정하였다. 감귤원에서 유살된 자료와 녹차 또는 키위과원에서 얻은 자료를 기반으로 각각 감귤기반모형(y = 310.9x + 69.0, r2=0.99) 녹차기반모형(y = 285.7x + 84.1, r2=0.99)을 개발하였다. 각 모형의 예측값과 독립된 포장 실측자료와의 잔차자승합을 토대로 모형의 적합성을 평가하였으며, 녹차기반모형의 적합력이 좋았다. 본 예측모형을 통한 계산값과 실측치의 불일치에 대한 원인과 모형의 포장 활용도에 대하여 고찰하였다.

Recently, the mineral resource protection policies and regulations in production countries of natural resources including rare metals are becoming more stringent. Such environment makes which market has malfunction. In other word, those are not perfect or pure market. Therefore because each market of natural resources have special or unique characters, it is difficult to forecast their market prices. In this study, we constructed several models to estimate prices of natural resources using ARIMA and their business indices. And for examples, Indium and Coal were introduced.

PURPOSES : This study is to investigate the relationship of socioeconomic characteristics and road network structure with traffic growth patterns. The findings is to be used to tweak traffic forecast provided by traditional four step process using relevant socioeconomic and road network data. METHODS: Comprehensive statistical analysis is used to identify key explanatory variables using historical observations on traffic forecast, actual traffic counts and surrounding environments. Based on statistical results, a multiple regression model is developed to predict the effects of socioeconomic and road network attributes on traffic growth patterns. The validation of the proposed model is also performed using a different set of historical data. RESULTS : The statistical analysis results indicate that several socioeconomic characteristics and road network structure cleary affect the tendency of over- and under-estimation of road traffics. Among them, land use is a key factor which is revealed by a factor that traffic forecast for urban road tends to be under-estimated while rural road traffic prediction is generally over-estimated. The model application suggests that tweaking the traffic forecast using the proposed model can reduce the discrepancies between the predicted and actual traffic counts from 30.4% to 21.9%. CONCLUSIONS : Prediction of road traffic growth patterns based on surrounding socioeconomic and road network attributes can help develop the optimal strategy of road construction plan by enhancing reliability of traffic forecast as well as tendency of traffic growth.

We previously reported Pear Pest Forecasting Management System (PPFMS) for the Improvement of pass ratio of Korean exporting pears. It is consisted of regular field forecasting by pear farmers, meteorological data obtained by automatic weather station (AWS), an internet web page (http://pearpest.jnu.ac.kr/) as information collecting and providing ground, and information providing service. Currently, we are expanding this system to the area, Cheonan and Ansung, where pear orchards are organized into exportation-specific group. Further, the information obtained from field forecasting and AWS were up-loaded to under-constructing upgraded webpage (http://www.kpear.kr), with several pest/disease-related information. We hope this pest forecasting management system increases the pass ratio of Korean exporting pears throughout establishment of farmer-oriented forecasting, inspiring farmers’ effort for the prevention and forecasting of diseases and pests occurring at pear orchards.

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

본 연구는 RCP 4종 시나리오(RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5)를 적용하여 얻어진 2100년까지의 대기온도 상승값을 해수면 상승 계산방법 중에 하나인 반경험식법(Semi-empirical method)에 적용하여 해수면 상승치를 예측하였다. RCP 4종 시나리오에서 얻어진 결과에 따르면 모든 시나리오에서 해수면이 꾸준히 상승하고 있음을 알 수 있었다. 2050년도까지 RCP 4종 시나리오에 대한 해수면 상승의 차이가 최대 0.08 m 이내였으나 2100년도에는 최대 0.5 m까지 해수면 상승의 격차를 보이고 있었다. RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5 시나리오의 2100년도 해수면 예상 상승치는 각각 0.87 m, 1.21 m, 1.02 m, 1.36 m였다. RCP 8.5시나리오는 2060년 이후로 대기온도 상승치가 다른 시나리오에 비해 급상승하는데, 2100년 이후 다른 시나리오와의 해수면 상승 격차는 더 커질 것으로 예상된다. 단순한 비례식으로 추정하면, 2080년도에 RCP 4종 시나리오의 최대 격차가 0.21 m였으나 20년 후인 2100년에는 그 두 배가 넘는 최대 0.5 m였다. 따라서 2120년에는 그 격차가 1.2 m 이상 될 수도 있다.

본 시험은 온도 발육모델을 이용하여 꽃매미 알의 부화시기를 예측하고 약충과 성충 방제에 효과적인 친환경 자재선발 및 끈끈이트랩 색상별 유인효과를 찾기 위하여 수행하였다. 꽃매미 알은 15, 20, 25℃(14L:10D)에서 각각 55.9, 26.8, 21.6일 만에 부화하였고 부화율은 각각 61.9, 57.8, 30.4%로 온도가 높을수록 부화소요기간은 짧고 부화율은 낮았다. 알의 온도와 발육속도와의 관계식은 Y=0.0028X-0.0228 (R2=0.9561)이었으며, 발육영점온도는 8.14℃, 유효적산온도는 355.4일도였다. 위의 관계식에 의하여 전남지역 꽃매미 알의 부화시기는 5월 22일로 예측되었다. 꽃매미 약충방제에 효과적인 친환경자재는 제충국추출물, 고삼추출물, 데리스추출물이었고, 성충은 제충국추출물, 고삼추출물이었다. 황토색, 파랑색, 노랑색 끈끈이트랩 중에서 황토색끈끈이트랩의 유인량은 2주 동안에 약충 535마리, 성충 87.7마리였다. 황토색 끈끈이트랩은 꽃매미 약충과 성충의 유인포살효과가 우수하였다.

We developed an age-based spawner-recruit model incorporating environmental variables to forecast stock biomass and recruits of pelagic fish in this study. We applied the model to the Tsushima stock of jack mackerel, which is shared by Korea and Japan. The stock biomass of jack mackerel (Trachurus japonicus) around Korean waters ranged from 141 thousand metric tons (mt) and 728 thousand mt and recruits ranged from 27 thousand mt to 283 thousand mt. We hind-casted the stock biomass to evaluate the model performance and robustness for the period of 1987~2009. It was found that the model has been useful to forecast stock biomass and recruits for the period of the lifespan of fish species. The model is also capable of forecasting the long-term period, assuming a certain climatic regime.

Fish communities in river networks provide significant ecosystem services that will likely decline under future land use and climate change. We developed a model that simulates the consequences to multiple populations of one or more fish species-a metacommunity- from multiple stressors across a river network. The model is spatiallyexplicit and age-structured, with three components: habitat suitability; population dynamics, including species interactions; and movement across a spatial network. Although this model is simple, it can form the basis of fisheries assessments and may be incorporated into an integrated modeling system for watershed management and prediction.

The restrictions and conditions of parcel delivery services are different from other delivery services. There is WTD in the parcel delivery service. WTDs are various along the types of buildings and delivery points. To make the problem solving method simple and efficient using the WTD, the values are observed and grouped based on the type of buildings in this research. Efficient VRP heuristic design could be possible with introduction of WTD concept as well as the delivery time forecasting.

Using artificial neural network (ANN) technique, auction prices for common mackerel were forecasted with the daily total sale and auction price data at the Busan Cooperative Fish Market before introducing Total Allowable Catch (TAC) system, when catch data had no limit in Korea. Virtual input data produced from actual data were used to improve the accuracy of prediction and the suitable neural network was induced for the prediction. We tested 35 networks to be retained 10, and found good performance network with regression ratio of 0.904 and determination coefficient of 0.695. There were significant variations between training and verification errors in this network. Ideally, it should require more training cases to avoid over-learning, which leads to improve performance and makes the results more reliable. And the precision of prediction was improved when environmental factors including physical and biological variables were added. This network for prediction of price and catch was considered to be applicable for other fishes.

 ,  , The developmental period of Laodelphax striatellus Fallen, a vector of rice stripe virus (RSV), was investigated at ten constant temperatures from 12.5 to 35±1℃ at 30 to 40% RH, and a photoperiod of 14:10 (L:D) h. Eggs developed successfully at each temperature tested and their developmental time decreased as temperature increased. Egg development was fasted at 35℃(5.8 days), and slowest at 12.5℃ (44.5 days). Nymphs could not develop to the adult stage at 32.5 or 35℃. The mean total developmental time of nymphal stages at 12.5, 15, 17.5, 20, 22.5, 25, 27.5 and 30℃ were 132.7, 55.9, 37.7, 26.9, 20.2, 15.8, 14.9 and 17.4 days, respectively. One linear model and four nonlinear models (Briere 1, Lactin 2, Logan 6 and Poikilotherm rate) were used to determine the response of developmental rate to temperature. The lower threshold temperatures of egg and total nymphal stage of L. striatellus were 10.2℃ and 10.7℃, respectively. The thermal constants (degree-days) for eggs and nymphs were 122.0 and 238.1DD, respectively. Among the four nonlinear models, the Poikilotherm rate model had the best fit for all developmental stages (r<, SUP>, 2<, /SUP>, =0.98∼0.99). The distribution of completion of each development stage was well described by the two-parameter Weibull function (r<, SUP>, 2<, /SUP>, =0.84∼0.94). The emergence rate of L. striatellus adults using DYMEX<, SUP>, ®<, /SUP>, was predicted under the assumption that the physiological age of over-wintered nymphs was 0.2 and that the Poikilotherm rate model was applied to describe temperature-dependent development. The result presented higher predictability than other conditions.

In this study, a forecasting engine from the user perspective is studied and developed. Characteristics of forecasting engine can be divided into a few categories, an algorithms for predicting variety of situations and the depth of algorithms based on the

기상 예보는 에너지 산업과 같은 다양한 산업 활동에 필수적인 정보를 제공한다. 본 연구의 목적은 에너지 산업을 대상으로 장기 기상 예보에 활용될 수 있는 GIS 기반의 프로토타입 시스템을 개발하는 것이다. 이를 위해 먼저 기상 및 기후 정보의 활용에 있어 GIS가 갖는 함의를 살펴보았다. 이어 현재 기상청에서 제공 중인 장기 예보 서비스에 대한 현황 분석 등을 토대로 활용 시스템의 발전 방향을 논의하였다. 여기에서는 에너지 산업을 고려하여 정보 자체의 발전 방안과 정보의 서비스 방식에 대한 개선 방안을 함께 검토하였다. 이를 토대로 장기 예보 정보의 활용을 위한 프로토타입 시스템을 데스크톱 GIS를 기반으로 개발하였다. 본 연구에서 개발된 시스템을 통해 GIS는 장기 예보 정보의 관리에서 서비스까지의 전 과정에서 매우 효과적이고 효율적인 기반이 될 수 있음을 확인하였다.

Grapholita molesta, G. dimorpha and C. sasakii as “internal feeders” are important apple pests in Korea. Three species overwinters around and in apple orchards. New young larvae of three species bore into new shoots or fruits and then feed inside apple. When mature larvae escape from fruits they make holes that reduces the commercial value of fruit. Therefore, understanding the phenological distribution of three species is critical to establish the precise management system for reducing three species population. The study was conducted to investigate the adult emergence of G. molesta, G. dimorpha and C. sasakii using pheromone traps and to forecast the cumulative proportion of each population. This study is second part of consecutive experiment. Data collection was carried out on three commercial apple orchards and one experimental orchard of Giran in 2010 and 2011. The experimental process was same in the study of plum. More than 50% of G. molesta male was occurred in spring season (within 500 degree-days), 2010 and 2011. The adult emergence of G. dimorpha and C. sasakii was linear and sigmoidal pattern in each year. The phenology of C. sasakii was explained well by nonlinear functions and the equation 3, 6, 8 and 11 were selected based on AICc and BIC. The selected equations were validated by the data of present year (2011) in each region. The performance of G. molesta and G. dimorpha was analyzed well by bimodal functions. The importance of phenological model is discussed to develop and maintain a more precise system for multiple pest management on apple orchard.

The study was conducted to investigate the phenological distribution of G. molesta, G. dimorpha and C. sasakii and to estimate the emergence timing of three species in plum orchards. It was known that G. molesta and G. dimorpha are a multi-voltine insect and C. sasakii has one to two generations depending on temperature and geographic location. Three species damage to many economically important fruit tree such as plum, pear, peach and apple. The main emergence time of each species is different depending on host plant and environmental conditions, specially temperature. Therefore, if we have the information of population density and low temperature threshold of a species and air mean temperature of a region in previous year we can predict the phenology of a species in present year. This is one part of consecutive research. Data collection was carried out in seven plum-growing commercial orchards of Uiseong in 2010 and 2011. The commercial pheromone monitoring traps (GreenAgroTech) were used to investigate the flight phenology of three speices. The record of temperature was received from meteorological center close to monitoring orchards. The relationships between degree-day accumulated above the low temperature threshold and cumulative proportion of accumulated moth caught of previous year was used to predict the phenology of three species in present year. The results of G. molesta and G. dimorpha estimated by bimodal functions were better than those analyzed by nonlinear functions. The phenology of C. sasakii was analyzed well by nonlinear function and the equation 3, 6, 8 and 11 were selected based on AICc and BIC. The selected equations were validated in each orchard.

Since 'The Act on Private Investment of The Infrastructure' was established in 1994, private investment as well as government's investment in transport infrastructure has been active. However investment in transport infrastructure has more risks than others' due to uncertainty both in traffic volume and in construction cost. In the current appraisal procedure of deciding transportation infrastructure investment, instead of risk management, the sensitivity analysis considering only the changes of benefit, cost and social discount rate which are main factor affecting economic feasibility is carried out. Therefore the uncertainty of various factors affecting demand, cost and benefit are not considered in feasibility study. In this study the problems in current investment appraisal system were reviewed. Using Delphi technique the major factors which have high uncertainty in feasibility study were surveyed and then improvement plan was suggested in the respective of classic 4 step demand forecasting method. The range estimation technique was also mentioned to deal with the uncertainty of the future.