Deep Data Stream Analysis Model and Algorithm With Memory Mechanism
نویسندگان
چکیده
منابع مشابه
Data Stream Linkage Mechanism
(DSLM), a program can be built by linking program modules to form a network through which data passes. The network is speciJed by the program designer using a mixture of pre-coded and custom coded modules. This linkage technique and the capabilities that result from it constitute an approach to programming that is radically diferent from conventional techniques. It can increase the productivity...
متن کاملSBM extended model with nonlinear value data in data envelopment analysis with axiomatic approach
One of the important goals of banks as important economic enterprises of any country is to increase economic efficiency. One of the important goals of banks as important economic enterprises of any country is to increase economic efficiency. The classical approach to data envelopment analysis models takes into account the linear valuation function for all indicators. But linear valuation in man...
متن کاملIntegration of remote sensing and meteorological data to predict flooding time using deep learning algorithm
Accurate flood forecasting is a vital need to reduce its risks. Due to the complicated structure of flood and river flow, it is somehow difficult to solve this problem. Artificial neural networks, such as frequent neural networks, offer good performance in time series data. In recent years, the use of Long Short Term Memory networks hase attracted much attention due to the faults of frequent ne...
متن کاملA Data Envelopment Analysis Model with Triangular Intuitionistic Fuzzy Numbers
DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of cri...
متن کاملDual Memory Architectures for Fast Deep Learning of Stream Data via an Online-Incremental-Transfer Strategy
The online learning of deep neural networks is an interesting problem of machine learning because, for example, major IT companies want to manage the information of the massive data uploaded on the web daily, and this technology can contribute to the next generation of lifelong learning. We aim to train deep models from new data that consists of new classes, distributions, and tasks at minimal ...
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: IEEE Access
سال: 2017
ISSN: 2169-3536
DOI: 10.1109/access.2016.2613922