A systematic review on data scarcity problem in deep learning: solution and applications
Recent advancements in deep learning architecture have increased its utility in real-life
applications. Deep learning models require a large amount of data to train the model. In …
applications. Deep learning models require a large amount of data to train the model. In …
Recommendation system based on deep learning methods: a systematic review and new directions
A Da'u, N Salim - Artificial Intelligence Review, 2020 - Springer
These days, many recommender systems (RS) are utilized for solving information overload
problem in areas such as e-commerce, entertainment, and social media. Although classical …
problem in areas such as e-commerce, entertainment, and social media. Although classical …
Photovoltaic power forecasting based on GA improved Bi-LSTM in microgrid without meteorological information
Due to flexible and clean nature, distributed photovoltaic (PV) power plants in micro-grid are
essential for solving energy and environmental problems. However, because of the high …
essential for solving energy and environmental problems. However, because of the high …
Effective long short-term memory with differential evolution algorithm for electricity price prediction
Electric power, as an efficient and clean energy, has considerable importance in industries
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …
Deep learning model for Demolition Waste Prediction in a circular economy
LA Akanbi, AO Oyedele, LO Oyedele… - Journal of Cleaner …, 2020 - Elsevier
An essential requirement for a successful circular economy is the continuous use of
materials. Planning for building materials reuse at the end-of-life of buildings is usually a …
materials. Planning for building materials reuse at the end-of-life of buildings is usually a …
Time series prediction for output of multi-region solar power plants
Solar energy, as a renewable and clean energy source, has developed rapidly and has
attracted considerable attention. The integration of solar energy into a power grid requires …
attracted considerable attention. The integration of solar energy into a power grid requires …
[HTML][HTML] 基于粒子群优化LSTM 的股票预测模型
宋刚， 张云峰， 包芳勋， 秦超 - 2019 - html.rhhz.net
为了提高股票时间序列预测精度, 增强预测模型结构参数可解释性, 提出一种基于自适应粒子群
优化(PSO) 的长短期记忆(LSTM) 股票价格预测模型(PSO-LSTM), 该模型在LSTM …
优化(PSO) 的长短期记忆(LSTM) 股票价格预测模型(PSO-LSTM), 该模型在LSTM …
Stock prediction based on genetic algorithm feature selection and long short-term memory neural network
S Chen, C Zhou - IEEE Access, 2020 - ieeexplore.ieee.org
In the financial market, there are a large number of indicators used to describe the change of
stock price, which provides a good data basis for our stock price forecast. Different stocks …
stock price, which provides a good data basis for our stock price forecast. Different stocks …
Deep learning based classification of unsegmented phonocardiogram spectrograms leveraging transfer learning
Objective. Cardiovascular diseases (CVDs) are a main cause of deaths all over the world.
This research focuses on computer-aided analysis of phonocardiogram (PCG) signals …
This research focuses on computer-aided analysis of phonocardiogram (PCG) signals …
Biomedical text summarization using conditional generative adversarial network (CGAN)
Text summarization in medicine can help doctors for reducing the time to access important
information from countless documents. The paper offers a supervised extractive …
information from countless documents. The paper offers a supervised extractive …