The accuracy of Inverse Distance Weighting （IDW） will be affected by the selection of reference points and parameters. Aiming at the problem of ignoring local characteristics in multi-Parameter co-optimization Inverse Distance Weighting algorithm （PIDW）， an improved algorithm based on particle swarm local optimized IDW was proposed， namely Particle swarm Local optimization Inverse Distance Weight （PLIDW）. Firstly， the parameters of each sample point in the study area were optimized respectively， and the cross-validation method was used for evaluation， and the optimal set of parameters for each sample point was recorded. At the same time， in order to improve the query efficiency， a K-Dimensional Tree （KD-Tree） was used to save the spatial positions and optimal parameters. Finally， according to the spatial proximity， the nearest set of parameters was selected from KD-Tree to optimize IDW. Experimental results based on simulated data and real temperature dataset show that compared with PIDW， PLIDW has the accuracy on the real dataset improved by more than 4.18%. This shows that the low accuracy in some scenarios caused by ignoring local features in PIDW is improved by the proposed algorithm， and the adaptability is increased at the same time.

In the digital Instrumentation Landing System (ILS) transformation, aiming at the problem that the ILS adopts the amplitude angle measuring system and is sensitive to the distortion of the amplitude of the transmitted signal, a calibration algorithm of the transmission channel of the digital ILS was proposed. Firstly, the mathematical model of the transmitter's landing system was established, and the effect of the non-linearity of the transmission channel on the angular performance of the ILS was simulated. Secondly, a transmitter structure with a feedback loop in the digital instrumentation landing system was proposed. Finally, the transmission channel was calibrated by solving the inverse model of the transmission channel in the baseband using the Least Mean Square (LMS) algorithm, and using the inverse model to compensate the nonlinear distortion of the transmission channel. The simulation results show that the proposed algorithm can quickly estimate the inverse model of the transmission channel under noise conditions and has good calibration performance.

Concerning the optimization of the overall complexity problem on the high-performance computing platform, a new algorithm named Group Mosquito Host-Seeking Algorithm (GMHSA) was proposed. GMHSA was an intelligent optimization algorithm inspired by mosquitoes sucking blood behavior. It involved max-min fairness and group interaction behavior. The producer group was chosen according to the concept of leader decision and the leadership functions were constructed to make each group maintain their own superiority as well as getting rid of local optimal solution. The algorithm was tested by Traveling Salesman Problem (TSP) and compared with other swarm intelligent algorithms. In the parallel experiment of 16 nodes, the speedup of GMHSA was 15.8, which was nearly linear speedup. Moreover, it could be directly used to solve transport problems and other practical optimal problems. The results indicate that GMHSA has highly parallelism and scalability, and it is an effective measurement for solving complex optimal problems involving behavior.

To remove the multiplicative noise better, a new three-stage method for multiplicative noise removal was proposed. In the first stage, log-image was processed by adaptive Steer Kernel Regression (SKR). Then in the second stage, the Total Variation (TV) regularization method was used to amend the image obtained. At last, via an exponential function and bias correction, the result was transformed back from the log-domain to the real one. The new method combined the advantages of steer kernel regression and total variation method. The experimental results show that the new method is more effective to filter out multiplicative noise.

The J2EE technologies and MVC design pattern was analyzed.Using MVC design pattern in the development of software,the process of developing software can be simplified,and the quality and the maintainability of software can be improved.Those techniques were used to implement a system of the Office Log.