CNN-Bi-LSTM: A Complex Environment-Oriented Cattle Behavior Classification Network Based on the Fusion of CNN and Bi-LSTM. [PDF]
Sensors (Basel), 2023 Cattle behavior classification technology holds a crucial position within the realm of smart cattle farming. Addressing the requisites of cattle behavior classification in the agricultural sector, this paper presents a novel cattle behavior classification network tailored for intricate environments.
Gao G +8 more
europepmc +4 more sources
AM-Bi-LSTM: Adaptive Multi-Modal Bi-LSTM for Sequential Recommendation
IEEE AccessConventional methods for the early fusion of multi-modal features cannot recognize the relevant modality corresponding to the demand of each user in sequential recommendation.
Kazuma Ohtomo +3 more
doaj +2 more sources
State-of-Charge Estimation of Lithium-Ion Batteries Based on the CNN-Bi-LSTM-AM Model Under Low-Temperature Environments [PDF]
SensorsAccurate state-of-charge (SOC) estimation is essential for lithium-ion battery management, especially under low temperatures where traditional methods suffer from noise sensitivity and nonlinear dynamics.
Ran Li +3 more
doaj +2 more sources
Predictive Analysis of Linoleic Acid in Red Meat Employing Advanced Ensemble Models of Bayesian and CNN-Bi-LSTM Decision Layer Fusion Based Hyperspectral Imaging [PDF]
FoodsRapid non-destructive testing technologies are effectively used to analyze and evaluate the linoleic acid content while processing fresh meat products. In current study, hyperspectral imaging (HSI) technology was combined with deep learning optimization ...
Xiuwei Yan +10 more
doaj +2 more sources
Research on Fault Prediction Method of Electronic Equipment Based on Bi-LSTM [PDF]
Hangkong bingqi, 2022 In order to improve the accuracy of electronic equipment fault prediction results, a fault prediction method based on bi-directional long short term memory (Bi-LSTM) is proposed.
Ni Xianglong, Shi Chang’an, Ma Yueliang, Liu Lei, He Jian
doaj +1 more source
Smart wearable sensor-based model for monitoring medication adherence using sheep flock optimization algorithm-attention-based bidirectional long short-term memory (SFOA-Bi-LSTM) [PDF]
Digital HealthObjective Medication adherence (MA) is crucial to patient treatment and vital for therapeutic outcomes. Due to its ability to continuously monitor a patient's MA behavior, the recent focus on sensor technology for MA monitoring is a promising development.
Yasser Alatawi +9 more
doaj +2 more sources
Deep Bi-LSTM Networks for Sequential Recommendation [PDF]
Entropy, 2020 Recent years have seen a surge in approaches that combine deep learning and recommendation systems to capture user preference or item interaction evolution over time. However, the most related work only consider the sequential similarity between the items and neglects the item content feature information and the impact difference of interacted items on
Chuanchuan Zhao +3 more
openaire +3 more sources
Agronomy, 2022 Precise forecasting of reference evapotranspiration (ET0) is one of the critical initial steps in determining crop water requirements, which contributes to the reliable management and long-term planning of the world’s scarce water sources.
Dilip Kumar Roy +9 more
doaj +1 more source
Analysis of hyperparameters in Sentiment Analysis of Movie Reviews using Bi-LSTM [PDF]
ITM Web of Conferences, 2022 Movie reviews are an important factor in determining a film’s success because instead of depending solely on the number of views as a parameter for the success of the movie, movie reviews are used to acquire additional insights into the movie.
Singh Amankumar +4 more
doaj +1 more source
Frontiers in Earth Science, 2023 Well log prediction while drilling estimates the rock properties ahead of drilling bits. A reliable well log prediction is able to assist reservoir engineers in updating the geological models and adjusting the drilling strategy if necessary.
Heng Wang +10 more
doaj +1 more source