Optimal control of cobalt crust seabedmining parameters based on simulated annealing genetic algorithm

Under the condition of the designated collection ratio and the interfused ratio of mullock, to ensure the least energy consumption, the parameters of collecting head （the feed speed, the axes height of collecting head, and the rotate speed） are chosen as the optimized parameters. According to the force on the cutting pick, the collecting size of the cobalt crust and bedrock and the optimized energy consumption of the collecting head, the optimized design model of collecting head is built. Taking two hundred groups seabed microtopography for grand in the range of depth displacement from 4.5 to 5.5 era, then making use of the improved simulated annealing genetic algorithm （SAGA）, the corresponding optimized result can be obtained. At the same time, in order to speed up the controlling of collecting head, the optimization results are analyzed using the regression analysis method, and the conclusion of the second parameter of the seabed microtopography is drawn.

Research on relations between failure heights of overburden strata and ~] / mining face parameters and forecasting method

The commercial FEM software ANSYS was used to analyze the failure characteristics of overburden strata under the conditions of different lengths of mining faces. It was shown that the parameters of mining faces, especially the length was the important factor to the failure heights and shapes of overburden strata. Fuzzy mathematics and statistical methods were used to analyze the forecasting method of the failure height of overburden strata influenced by the parameters of mining face based on the measured data under the conditions of fully-mechanized mining of general hardness cover rocks. On the basis of these analyses, a new forecasting formula was gotten. The forecasting result conforms to the in situ measured value. The result has a very important application value in safe and high-efficient mining, and has a very important advancing function to theoretical studies.

Research on predicting prosodic parameters for Chinese synthesis by data mining approach

Prosodic control is an important part of speech synthesis system. Prosodic parameters choice right or wrong influences the quality of synthetic speech directly. At present, text to speech system has less effective describe to reflect data relationships in the corpus. A new research approach - data mining technology to discover those relationships by association rules modeling is presented. And a new algorithm for generating association rules of prosodic parameters including pitch parameters and duration parameters from corpus is developed. The output rules improve the correctness of syllable choice in text to speech system.