第一个前沿组中的个体是完全非支配个体,它们的rank值被赋为1。第二个前沿组中个体受第一个前沿组中的个体支配,它们的rank值被赋为2。其余前沿组中个体依次类推 。 NSGA2引入拥挤距离(crowding distance)作为评判个体与相邻个体间的远近的指标。拥挤距离越大说明种群里个体越分散。 NSGA2使用双锦标赛制的方式,根...
CNN-LSTM-Based Late Sensor Fusion for Human Activity Recognition in Big Data Networksdoi:10.1155/2022/3434100HUMAN activity recognitionSMART devicesBIG dataCONVOLUTIONAL neural networksUBIQUITOUS computingTECHNOLOGICAL innovationsThe technological advancement in sensor technology and pervasive computing ...
In this tutorial, you discovered how to diagnose the fit of your LSTM model on your sequence prediction problem. 在本教程中,您发现了如何在序列预测问题上诊断LSTM模型的拟合度。 Specifically, you learned: How to gather and plot training history of LSTM models. How to diagnose an underfit, good...
1. ncnn https://github.com/Tencent/ncnn 2. crnn https://github.com/meijieru/crnn.pytorch.git 3. chineseocr https://github.com/chineseocr/chineseocr 4. Psenet https://github.com/WenmuZhou/PSENet.pytorch 5. 语言模型实现 https://github.com/lukhy/masr 0 comments on commit 8ac81...
BIG DataDeep LearningCNNLSTMMISMOTEAutomatic and accurate prognosis of myocardial infarction (MI) using electrocardiogram (ECG) signals is a challenging task for the diagnosis and treatment of heart diseases. MI is also referred as a "Heart Attack", which is the most fatal cardiovascular disease. ...
RETRACTED ARTICLE: Integrated CNN- and LSTM-DNN-based sentiment analysis over big social data for opinion miningP. KaladeviK. Thyagarajah
It is important to the early prediction using the HCNN-LSTM Algorithm using Big Data technology. According to the IDF report, the patients' records are huge volume, to manage and store all patients' records HDFS storage is required and it is under the big data technology.T. Papitha ...
For this reason, a deep CNN with reinforcement-LSTM model is proposed for forecasting stock future prices based on big data. Furthermore, four real-time stock future prices such as NASDAQ, FTSE, TAIEX, and BSE are used for analyzing the efficiency of the proposed deep CNN with reinforcement-...
Integrated CNN- and LSTM-DNN-based sentiment analysis over big social data for opinion miningdoi:10.1080/0144929X.2019.1699960P. KaladeviK. ThyagarajahBehaviour and Information Technology
LSTM模型注意力机制组合模型为了对盗窃犯罪时空分布进行预测,解决传统的LSTM准确率较低的问题,文章提出将CNN-LSTM-Attention模型用以解决盗窃犯罪预测问题,并结合社区和环境影响因素,实现以"日"为时间尺度,以"社区"为空间尺度,以"温度""天气"为环境因素预测,并运用该模型对N市,S市,C市,O市,P市的盗窃案件案发数量...