Results 51 to 60 of about 12,226 (126)

A Mathematical Framework for E-Commerce Sales Prediction Using Attention-Enhanced BiLSTM and Bayesian Optimization

Mathematical and Computational Applications
Accurate sales prediction is crucial for inventory and marketing in e-commerce. Cross-border sales involve complex patterns that traditional models cannot capture.
Hao Hu, Jinshun Cai, Chenke Xu
doaj   +1 more source

Development of Artificial Intelligence/Machine Learning (AI/ML) Models for Methane Emissions Forecasting in Seaweed

Methane
This research project aimed to address the growing concern about methane emissions from seaweed by developing a Convolutional Neural Network (CNN) model capable of accurately predicting these emissions.
Clifford Jaylen Louime, Tariq Asleem Raza   +1 more
doaj   +1 more source

IS THE BOX-COX TRANSFORMATION NEEDED IN MODELING TELKOM’S STOCK PRICE USING NNAR AND DESH METHODS?

Media Statistika
Accurate stock price forecasting requires appropriate preprocessing, particularly for time series data with high variability and nonlinear patterns.
Michela Sheryl Noven, Respatiwulan Respatiwulan, Winita Sulandari   +2 more
doaj   +1 more source

A hybrid deep learning and tree based approach to forecast AQI in indoor environments

Environmental Research Communications
The attendance, well-being and comfort of students is directly affected by the air quality in the classroom. Additionally, the performance of teachers and staff is also impacted by it.
Anurag Barthwal, Shwetank Avikal
doaj   +1 more source

Comparing Optimization Algorithms in ANN Models for House Price Prediction in Pekanbaru

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This study evaluates the performance of five optimization algorithms in Artificial Neural Network (ANN) models for predicting house prices in Pekanbaru. The optimizers tested include Adam, AdaDelta, Stochastic Gradient Descent (SGD), Nadam, and Adaptive
Doni Winarso, Edo Arribe, Syahril, Aryanto, Muhardi, Shahrulniza Musa   +5 more
doaj   +1 more source

A Unified Family of Percentage-Error Support Vector Regression Models with Symmetric Kernel Extensions

Mathematics
Support vector regression (SVR) is a well-established kernel-based method for nonlinear regression. However, standard SVR formulations minimize absolute-error losses, which are not consistent with the scale-free, relative-accuracy criteria prevalent in ...
Pablo Benavides-Herrera, Gregorio Álvarez, Riemann Ruiz-Cruz, Juan Diego Sánchez-Torres   +3 more
doaj   +1 more source

PERAMALAN NILAI TUKAR PETANI PROVINSI ACEH: DITINJAU DENGAN METODE DOUBLE EXPONENTIAL SMOOTHING DAN HOLT WINTER

Jurnal Lebesgue
This research aimed to compare the performance of the Double Exponential Smoothing and Holt-Winter methods in forecasting the Farmer Exchange Rate (NTP) for the Horticulture Farmer Subsector in Aceh Province.
Zulfa Razi, Mirunnisa Mirunnisa, Maryanti Maryanti, Nurhayati Nurhayati   +3 more
doaj   +1 more source

Modification of Multilayer Perceptron Using Detection Rate Model for Prediction of Nominal Exchange Rate

Journal of Applied Engineering and Technological Science
An artificial neural network (ANN) is a network of a group of units to be processed which is modeled based on the behavior of human neural networks. ANN has one of its tasks, namely prediction.
Al-Khowarizmi Al-Khowarizmi, Romi Fadillah Rahmat, Michael J Watts, Akrim Akrim, Arif Ridho Lubis, Muhammad Basri   +5 more
doaj   +1 more source

Accuracy Evaluation of Multi-Factor Forecasting Methods for Customer Service Workload Prediction Under Holiday and Promotional Fluctuations: Evidence from U.S. Service Industry Data

Journal of Advanced Computing Systems
Accurate prediction of customer service workload is essential for workforce scheduling and resource allocation in the U.S. service industry. This study conducts a comparative evaluation of four forecasting approaches—Seasonal Autoregressive Integrated ...
Yajing Zhang, Minhao Li
doaj   +1 more source

Validity and reliability of the Tianyu climbing machine in maximal oxygen uptake testing. [PDF]

Front Physiol
Yang F, Liu W, Wu T, He H, Xun H.
europepmc   +1 more source