Research And Application On Computational Intelligence In Data Fusion Of Soil Information

Multi-sensor data fusion technology was developed firstly from the military area, and had been developed into a new subject direction and research field.In this paper, the definition and the model of data fusion were introduced together with its development and research status.Studied the uncertain methods of the data fusion.Combined with the research at the National"863"major projects—the key information and product development of express collection of soil information, Constructed the model of soil parameters.On the base of the theory of computational intelligence, New ideas were put forward based on multi-sensor data fusion algorithm and the thorough research had been done.Do some research on data fusion model and algorithm combined with BP and belief function.Build belief function matrix and use it to measure the belief degree of sensor data.Distribute the weight of the fusion process reasonably which is the input of BP neural network.The fusion effect is good through the best trained network which weaks the white noise of measurement accuracy while at the same time a number of sensor observation value were compressed into an optimal fusioned data.Two sensor fusion algorithms were given based on particle swarm optimization (PSO).One method was to improve the inertia weight of PSO where the role of the inertia weight factor in PSO was analysed. A nonlinear strategy for DIW was put forward to the field of the multi-sensor fusion which can estimate the weight factor of the data fusion algorithm and get closer to the ture value. The other method is to use multi-sensor data fusion algorithm based on QDPSO-BP network, throgh which trained BP neural network and got good stability and convergence.Higher accuracy would be gotten by using it in the simulation.It is a potential data fusion method for multi-sensors.Research the character of wavelet transform.The multi-resolution and multi-sensor data fusion model was proposed based on wavelet packet.Research the new multi-sensor data fusion algorithm in the pixel level, feature level by using the wavelet theory.Apply the data fusion algorithm to specific data processing combined the measurement parameters of the various fields. Analysis the soil moisture content, conductivity and other parameters actually. Extract the biochemistry and biophysics parameters from valuable crops and guide the agricultural production and management so as to enhance crop yield and quality.Provide a theoretical base on precision agriculture for the further implementation.