Medical disease prediction using Grey Wolf optimization and auto encoder based recurrent neural network
نویسندگان
چکیده
منابع مشابه
Auto-encoder pre-training of segmented-memory recurrent neural networks
The extended Backpropagation Through Time (eBPTT) learning algorithm for Segmented-Memory Recurrent Neural Networks (SMRNNs) yet lacks the ability to reliably learn long-term dependencies. The alternative learning algorithm, extended Real-Time Recurrent Learning (eRTRL), does not suffer this problem but is computational very intensive, such that it is impractical for the training of large netwo...
متن کاملRegistration of Point Clouds based on Global Super-Point Features using Auto-Encoder Deep Neural Network
Registration of scanned point clouds is the process of integrating two separate local point clouds into one global coordinate system. This process is a key stage in robotic vision SLAM[1], [2], 3D scan to model matching[3] and precision navigation with noisy GPS input. New data acquisition technology such as LIDAR laser scanners mounted on vehicle or aircraft enables for the capture of high qua...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Texture Synthesis with Recurrent Variational Auto-Encoder
We propose a recurrent variational auto-encoder for texture synthesis. A novel loss function, FLTBNK, is used for training the texture synthesizer. It is rotational and partially color invariant loss function. Unlike L2 loss, FLTBNK explicitly models the correlation of color intensity between pixels. Our texture synthesizer 1 generates neighboring tiles to expand a sample texture and is evaluat...
متن کاملGear Remaining Useful Life Prediction Based on Grey Neural Network
The condition monitoring data of gears is asymmetric distributed, moreover, sampling is usually conducted discontinuously in practice. Thus makes it difficult to predict gear remaining useful life accurately considering the two reasons above. In this paper, a fusion method is proposed using Elman Neural Network to modify residual series of grey model since Elman Neural Network performs better o...
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: Periodicals of Engineering and Natural Sciences (PEN)
سال: 2018
ISSN: 2303-4521
DOI: 10.21533/pen.v6i1.286