Weather based statistical model

The study was based on, an application of discriminant function analysis of Agroclimatic zone for developing suitable statistical models to forecast wheat yield in Ayodhya district of Eastern Utter Pradesh has been demonstrated. The study utilized the crop yield data and corresponding weekly weather data of last 27 years (1990-91 to 2016-17).

7p trinhthamhodang11 27-04-2021 14 1   Download

The weather variables affect the crop differently during various stages of development (Tripathi et al., 2012). Thus, extent of weather influence on crop yield depends not only on the magnitude but also on the distribution pattern of weather variables over the crop season.

7p nguaconbaynhay7 15-08-2020 6 1   Download

Parameter estimation in statistical modelling plays a crucial role in the real world phenomena. Several alternative analyses may be required for the purpose. An attempt has been made in this paper to estimate the yield of wheat crop using principal components of the weather parameters spread over the crop growth period. Principal component analysis has been used for the purpose of developing zonal yield forecast models because of multicollinearity present among weather variables.

6p nguaconbaynhay6 23-06-2020 9 0   Download

Climate change and agriculture are interrelated processes, both of which take place on a global scale. The study was undertaken to identify the trend in weather parameters in Malaprabha Command Area (MCA). The research was based on secondary data of nineteen years (1999 to 2017) on different weather parameters such as precipitation, temperature, relative humidity and potential evapotranspiration obtained from the Irrigation Water Management Research Centre, Belavatgi under UAS, Dharwad.

9p quenchua6 15-06-2020 12 1   Download

The present investigation entitled “Forecast Models of Potato Yield Using Principal Component Analysis for Sultanpur District of Eastern Uttar Pradesh.” Time series data on yield of potato and weekly data from 40th SMW of the previous year to 6th SMW of the following year on five weather variables viz., Minimum Temperature, Maximum Temperature, Relative humidity 08.30hrs, Relative humidity 17.30hrs, and Wind-Velocity covering the period from 1990-91 to 2011-12 have been utilized for development of preharvest forecast model.

6p trinhthamhodang5 16-05-2020 10 0   Download

Pre harvest crop yield forecast is required for storage, pricing, marketing, import, export etc. Weather is the main factor which affects crop yield. Variability in weather causes the losses in the yield. Use of weather can be done for crop production forecast. Weather plays an important role in crop growth. Therefore model based on weather parameters can be provide reliable forecast in advance for crop yield. In this study, the focus was on the development crop yield forecast (CYF) model through stepwise linear regression technique using weather variables and historic crop yield.

4p caygaocaolon4 01-04-2020 11 1   Download

The estimation of crop yield before harvest helps in different policy making in an order for storage, distribution, marketing, pricing, import-export etc. Crop productions depend on several factors such as weather factors, plant characters and agricultural inputs. The present study was carried out to develop the appropriate statistical model for estimation of rice yield before harvest in the year 2018-19. This research was done on plant biometrical characters along with farmer’s appraisal.

10p nguathienthan3 27-02-2020 27 0   Download

The growth of Indian economy mainly depends on agriculture sector as it accounts 18 percent of national GDP. Agriculture sector was one of the main area to impact by climate change. Pre-harvest forecast based on weather parameters plays very important role in developing countries. Rice is the most significant principal food in India which play fundamental role in day-to-day requisite of diet. In the current study statistical crop modeling was engaged to provide forecast in advance.

12p kethamoi2 14-12-2019 19 0   Download

We present a novel PCFG-based architecture for robust probabilistic generation based on wide-coverage LFG approximations (Cahill et al., 2004) automatically extracted from treebanks, maximising the probability of a tree given an f-structure. We evaluate our approach using stringbased evaluation. We currently achieve coverage of 95.26%, a BLEU score of 0.7227 and string accuracy of 0.7476 on the Penn-II WSJ Section 23 sentences of length ≤20. grammar for generation.

8p hongvang_1 16-04-2013 54 2   Download

The hardness result for selecting an optimal index configuration was shown by Shapiro [60]. Therefore, the challenge was similar to that in the area of query optimization – identifying the right set of heuristics to guide the selection of physical design. One set of papers advocated an approach based on rule-based expert systems. The rules took into account query structures as well as statistical profiles and were “stand-alone” applications that recommended indexes. A tool such as DEC RdbExpert falls in this category.

13p yasuyidol 02-04-2013 55 3   Download