| 摘要 |
PROBLEM TO BE SOLVED: To output a report on an earthquake and a control signal prior to the arrival of a main movement of the earthquake by using an urgent earthquake prompt report, to perform not only the prompt report but also high-accuracy evaluation in consideration of a predominant period of the ground and the vibration characteristics of a building by using a neural network, and to dramatically enhance the reliability of prediction by optimizing the neural network by learning, as to earthquake disaster prevention for facilities, buildings, etc. SOLUTION: The quake or the level of damage at a target point is estimated prior to the arrival of the main movement of the earthquake by using the neural network that adopts, as input parameters, not only the magnitude at the seismic center, the position (longitude and latitude) of the seismic center, the depth of the seismic center, and the arrival time and size of earthquake motion, acquired from the urgent earthquake prompt report, but also dynamic characteristics such as the predominant period of the ground at an object point previously acquired by survey and, as to the interior of a building, the proper period, damping stories, etc. of the building, to perform reporting for earthquake disaster prevention or controlling on installations/equipment. Optimization is achieved by thereto adding a self-learning function. COPYRIGHT: (C)2006,JPO&NCIPI |
