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House price in Taipei city is a widely discussed issue. Generally, the price is decided by people's understanding from past dealing-price. In the past decades, many researchers pay attention on the study of house price prediction by computer computation. Recently, different machine learning models are adopted to analyze the actual price registration dataset for predicting house price. This study examines linear regression, MLP (Multi-layer perceptron), and LSTM (Long Short-Term Memory) models on prediction of the actual price registration dataset. Various parameters and combinations are also test in our experiments. Experimental results show that LSTM deep neural network has better prediction than others. In the selection of optimizer, the Adam function exhibits better than SGD or RMSProp functions. In our limited experiments, single-layer deep neural network model leads to better results than different multi-layer deep neural network models. [ABSTRACT FROM AUTHOR]

To monitor the fault activity in the Taipei area, a new broadband downhole seismic network comprised of three stations was established in the Taipei Basin over a period of three years, 2005 - 2007. The network geometry is a triangle with a station spacing of about 12 km covering the entire Taipei Basin. Each station has two holes of different depths containing modern instruments, including a low-gain broadband seismometer. The largest depth is 150 m. We report our first experience on the installation and operation of the broadband downhole seismic network in the Taipei Basin. Some representative records from the Pingtung earthquake doublet in December 2006 are shown here. Ground displacement during the Pingtung earthquake doublet can be recovered from the velocity records without the baseline corrections that are required for the acceleration records. Our network offers excellent data for accurate and effective characterization of seismic motion in the study area. Seismic data from this network will be shared with other research institutions in Taiwan and abroad for further research. [ABSTRACT FROM AUTHOR]