IMPLEMENTASI MODEL CONVOLUTIONAL RECURRENT NEURAL NETWORK (CRNN) DENGAN BIDIRECTIONAL LONG SHORT-TERM MEMORY (BI-LSTM) UNTUK PENGENALAN EMOSI PADA SUARA

Author

ADHIRAJASA M. RADITYA

University

Lampung University

Country

Indonesia

Main specialisation

Natural Language Processing › Sentiment Analysis

Pengenalan emosi pada suara merupakan tugas kompleks yang krusial untuk interaksi manusia-mesin. Penelitian ini mengimplementasikan dan mengevaluasi model Convolutional Recurrent Neural Network (CRNN) yang menggabungkan keunggulan Convolutional Neural Network…

Predicting Irregularities in Arrival Times for Toronto Transit Buses with LSTM Recurrent Neural Networks Using Vehicle Locations and Weather Data

Author

Anshuman Kush

University

Trent University

Country

Canada

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

Public transportation systems play important role in the quality of life of citizens in any metropolitan city. However, public transportation authorities face criticisms from commuters due to irregularities in bus arrival times. For example, transit bus users…

NORMALISASI DOKUMEN TEKS MENGANDUNG KATA MIXED-CODE UNTUK ANALISIS SENTIMEN DENGAN METODE RECURRENT NEURAL NETWORK LONG SHORT-TERM MEMORY (RNN-LSTM)

Author

ANJAS WIRANTA TARIGAN ; Erlanshari Aan ; Susanto Agus

University

University of Bengkulu

Country

Indonesia

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

A Deep Neural Network Approach Integrating CNN and BiLSTM-Transformer Architectures for Emotion Recognition from Speech

Author

Divyansh Anand

University

Not available

Country

Not available

Main specialisation

Deep Learning & Neural Networks › Transformers

The goal of speech emotion recognition is to make human-computer interaction more efficient in several areas such as customer service, entertainment industry, human-computer interaction, healthcare, and education. Previous work in speech emotion analysis prese…

Prediction of Blood Glucose Levels for Diabetic Patients from LSTM-Type Recurrent Neural Networks

Author

Ismael Vega Rojas

University

Universidad Industrial de Santander

Country

Colombia

Main specialisation

AI in Healthcare › Recurrent Neural Networks / LSTM

En este trabajo de grado se presenta un modelo de estimación de glucosa para pacientes con diabetes mellitus tipo 1, donde se usa el simulador T1DMS (Visentin et al., 2018) con el que se obtiene un conjunto de mediciones de insulina y glucosa para entrenar el…

LSTM recurrent neural network for identification of a thermal system

Author

Guilherme Nomura Mateus Leite

University

Federal University of Technology – Paraná

Country

Brazil

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

The focus of this graduation thesis is the application of a Long Short-Term Memory (LSTM) recurrent neural network (RNN) in the context of identifying and modeling a complex thermal system consisting of two heaters and two sensors. The proposed approach is bas…

Intra-day photovoltaic generation forecast using LSTM recurrent neural networks and historical energy data

Author

Bruno Rapchaell Magalhaes da Cunha

University

Not available

Country

Not available

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

Este trabalho apresenta uma metodologia que utiliza dados históricos de energia para obter a previsão de geração de sistemas fotovoltaicos no horizonte de 1h, utilizando o conceito de janela temporal (time steps) e uma rede recorrente do tipo LSTM (Long Short…

Predicting U.S. business cycles with recurrent neural networks : An extensive multivariate time-series analysis for comparing LSTM and GRU networks

Author

Markus M. Mäkelä

University

University of Turku

Country

Finland

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

This study examines how 22 different long short-term memory (LSTM) and gated recurrent unit (GRU) network architectures suit predicting U.S. business cycles. The networks create 91-day forecasts for the dependent variable by using multivariate time-series data…

Long Short-term Memory (LSTM) recurrent neural networks for urban hydrological modelling

Author

Vetle Øyri

University

Not available

Country

Norway

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

Time Series Forecasting of House Prices: An evaluation of a Support Vector Machine and a Recurrent Neural Network with LSTM cells

Author

Jako Rostami ; Fredrik Hansson

University

KTH Royal Institute of Technology

Country

Sweden

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

In this thesis, we examine the performance of different forecasting methods. We use dataof monthly house prices from the larger Stockholm area and the municipality of Uppsalabetween 2005 and early 2019 as the time series to be forecast. Firstly, we compare the…

Generating rhyming poetry using LSTM recurrent neural networks

Author

Cole Peterson

University

University of Victoria

Country

Canada

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

Current approaches to generating rhyming English poetry with a neural network involve constraining output to enforce the condition of rhyme. We investigate whether this approach is necessary, or if recurrent neural networks can learn rhyme patterns on their ow…

LSTM Neural Network Models for Market Movement Prediction

Author

Edwin Li

University

KTH Royal Institute of Technology

Country

Sweden

Main specialisation

Deep Learning & Neural Networks › Recurrent Neural Networks / LSTM

Interpreting time varying phenomena is a key challenge in the capital markets. Time series analysis using autoregressive methods has been carried out over the last couple of decades, often with reassuring results. However, such methods sometimes fail to explai…