Probabilistic neural network-based 2D travel-time tomography
نویسندگان
چکیده
منابع مشابه
Discrimination of Power Quality Distorted Signals Based on Time-frequency Analysis and Probabilistic Neural Network
Recognition and classification of Power Quality Distorted Signals (PQDSs) in power systems is an essential duty. One of the noteworthy issues in Power Quality Analysis (PQA) is identification of distorted signals using an efficient scheme. This paper recommends a Time–Frequency Analysis (TFA), for extracting features, so-called "hybrid approach", using incorporation of Multi Resolution Analysis...
متن کاملPersian Handwritten Digit Recognition Using Particle Swarm Probabilistic Neural Network
Handwritten digit recognition can be categorized as a classification problem. Probabilistic Neural Network (PNN) is one of the most effective and useful classifiers, which works based on Bayesian rule. In this paper, in order to recognize Persian (Farsi) handwritten digit recognition, a combination of intelligent clustering method and PNN has been utilized. Hoda database, which includes 80000 P...
متن کاملDesigning of a New Transformer Ground Differential Relay Based on Probabilistic Neural Network
Low- impedance transformer ground differential relay is a part of power transformer protection system that is employed for detecting the internal earth faults. This is a fast and sensitive relay, but during some external faults and inrush current conditions, may be exposed to maloperation due to current transformer (CT) saturation. In this paper, a new intelligent transformer ground differentia...
متن کاملWave-equation-based travel-time seismic tomography – Part 1: Method
In this paper, we propose a wave-equation-based travel-time seismic tomography method with a detailed description of its step-by-step process. First, a linear relationship between the travel-time residual 1t = T − T syn and the relative velocity perturbation δc(x)/c(x) connected by a finite-frequency travel-time sensitivity kernel K(x) is theoretically derived using the adjoint method. To accur...
متن کاملDeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision
Estimating the travel time of a path is of great importance to smart urban mobility. Existing approaches are either based on estimating the time cost of each road segment which are not able to capture many cross-segment complex factors, or designed heuristically in a non-learning-based way which fail to utilize the existing abundant temporal labels of the data, i.e., the time stamp of each traj...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computing and Applications
سال: 2020
ISSN: 0941-0643,1433-3058
DOI: 10.1007/s00521-020-04921-8