Yield prediction techniques based on DFM rules and criticality for 65nm technology and beyond

Author(s):  
Tsutomu Kojima ◽  
S. Kyou ◽  
H. Murakami ◽  
K. Honda ◽  
T. Nakayama ◽  
...  

Crop yield prediction is an art of forecasting the yield of crop before harvesting. Prediction of crop yield will be very useful for the government to make food policies, market price, import and export policies and proper warehousing well in time. The socio-economical impact of crop loss due to any natural disaster i.e. flood, drought can be minimized and humanitarian food assistance can be planned. The paper present a literature survey of various stastical method, empirical models,artificial neural network and machine learning regression techniques which are used with the data provided by the satellites. Many models are developed and results calculated are compared with the benchmark models are also presented.


Author(s):  
Sujata Mulik

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 


1997 ◽  
Author(s):  
D.L. Rockwood ◽  
B. Yang ◽  
K.W. Outcalt

1995 ◽  
Vol 32 (2) ◽  
pp. 297-304
Author(s):  
Willem A. M. Botes ◽  
J. F. Kapp

Field dilution studies were conducted on three “deep” water marine outfalls located along the South African coast to establish the comparibility of actual achievable initial dilutions against the theoretical predicted values and, where appropriate, to make recommendations regarding the applicability of the different prediction techniques in the design of future outfalls. The physical processes along the 3000 km long coastline of South Africa are diverse, ranging from dynamic sub-tropical waters on the east coast to cold, stratified stagnant conditions on the west coast. Fourteen existing offshore marine outfalls serve medium to large industries and various local authorities (domestic effluent). For this investigation three outfalls were selected to represent the range of outfall types as well as the diversity of the physical conditions of the South African coastline. The predicted dilutions, using various approaches, compared well with the measured dilutions. It was found that the application of more “simple” prediction techniques (using average current velocities and ambient densities) may be more practical, ensuring a conservative approach, in pre-feasibility studies, compared to the more detailed prediction models, which uses accurate field data (stratification and current profiles), when extensive field data is not readily available.


Author(s):  
Fatin Farhan Haque ◽  
Ahmed Abdelgawad ◽  
Venkata Prasanth Yanambaka ◽  
Kumar Yelamarthi

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