tailieunhanh - Hướng của điểm đặc trưng trên ảnh vân tay.

Hướng của điểm đặc trưng trên ảnh vân nghiên cứu chi tiết các đặc điểm địa chấn-kiến tạo, xác lập mối quan hệ mật thiết giữa động đất, núi lửa với các đứt gãy hoạt động; xác định được 12 đứt gãy sinh chấn, có khả năng tiềm ẩn nguy cơ động đất cực đại ≤ Mmax ≤ đối với các đứt gãy cấp 1, 2 và ≤ Mmax ≤ 55 đối với các đứt gãy cấp 3. Các đứt gãy Mãng Cầu-Phú Quý, Thuận Hải-Minh Hải và Hồng-Tây Mãng Cầu, phía Đông khu vực nghên. | Tạp chí Tin học và Điều khiển học T. 16 s. 2 2000 59-62 NEUTRAL NETWORK IN LITHOLOGY DETERMINATION LE HAI AN Abstract. Application of artificial neural network in lithology identification has been developed in the recent years and plays an important role in Petroleum Industry in general and well logs interpretation in particular. In this paper this ability of artificial neural network has been demonstrated by a case study conducted recently. 1. INTRODUCTION Artificial neural networks are computer models or computational systems which attempt to mimic the workings of the human brain. They can learn from examples and experiences and are extremely handy for automatically obtaining solutions of complex decision prediction control as well as classification problems. Up to this time neural network technology has been applied to solving many real-world problems with remarkable success in diverse areas such as Computer science Engineering Cognitive science Neurophysiology Physics and Biology. In the petroleum industry however the application of neural networks NN is not well known. This paper therefore is intended to introduce in brief how neural network can be applied in Petroleum industry in general and in well logs interpretation in particular by a case-study of lithology prediction which has been conducted by the author. 2. WHAT IS A NEURAL NETWORK Let us come back to clarity some concepts of a traditional NN. A NN is created with a serial or parallel analysis to simulate the interactions among neurons in a biological neural network. A NN is a computational system composed of nodes or neurons and the connections between these nodes in a complex manner via synapses. The NN can be programmed to recognize patterns retrieve data filter noise and complete missing information. They can learn generalize and interpret whereas traditional computing algorithms and statistical methods have been insufficient. The advantage of NN compared with sequential computer analysis where .