Results 31 to 40 of about 6,298,628 (254)

A Comparison of Models for Estimating Solar Radiation from Sunshine Duration in Croatia

International Journal of Photoenergy, 2020
The performance of seventeen sunshine-duration-based models has been assessed using data from seven meteorological stations in Croatia. Conventional statistical indicators are used as numerical indicators of the model performance: mean absolute ...
Tihomir Betti, Ivana Zulim, Slavica Brkić, Blanka Tuka   +3 more
doaj   +1 more source

Developing and Preliminary Testing of a Machine Learning-Based Platform for Sales Forecasting Using a Gradient Boosting Approach

Applied Sciences, 2022
Organizations engaged in business, regardless of the industry in which they operate, must be able to extract knowledge from the data available to them. Often the volume of customer and supplier data is so large, the use of advanced data mining algorithms
Antonio Panarese, Giuseppina Settanni, Valeria Vitti, Angelo Galiano   +3 more
doaj   +1 more source

Mean absolute percentage error (MAPE) and error range for the four activity monitors tested: all values ± 2SD from the mean observed step count excluded.

, 2016
Mean absolute percentage error (MAPE) and error range for the four activity monitors tested: all values ± 2SD from the mean observed step count excluded.
Orlaith Kilgannon (2742577), Leo R. Quinlan (2742571), Sandra O’Connell (2742574), Sorcha Beirne (2742580), Elaine Murphy (2742586), Niall Burke (407994), Lisa Kelly (2742589), Gearóid ÓLaighin (2742583)   +7 more
core   +1 more source

Programmable Variable‐Stiffness Multilayer Elastomer Composites With High‐Aspect‐Ratio Low‐Melting‐Point Alloy Inclusions

Advanced Materials Technologies, EarlyView.
High‐aspect‐ratio low‐melting‐point alloy inclusions are embedded within multilayer silicone laminates to create thermally programmable stiffness. Sequential activation of alloy‐rich layers produces four distinct mechanical states and reconfigures tendon‐driven actuator trajectories under the same load.
Palpolage Don Shehan Hiroshan Gunawardane, Gyan Edbert Zesiro, Hao Zhou, Gursel Alici, Mu Chiao   +4 more
wiley   +1 more source

New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods.

PLoS ONE
This research compared the efficiency of several adjusted missing value imputation methods in multiple regression analysis. The four imputation methods were the following: regression-ratio quartile1,3 (R-RQ1,3) imputation of Al-Omari, Jemain and Ibrahim;
Juthaphorn Sinsomboonthong, Saichon Sinsomboonthong   +1 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

A novel long-term water absorption and thickness swelling deep learning forecast method for corn husk fiber-polypropylene composite

Case Studies in Construction Materials, 2022
Investigating long-term water absorption (WA) and thickness swelling (TS) behaviors of wood plastic composites demand long working hours and high laboratory costs.
Ehsan Yousefi, Mostafa Barzegar Shiri, Mohammad Amin Rezaei, Sajad Rezaei, Shahab S. Band, Amir Mosavi   +5 more
doaj   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Comparison of Linear Regression and Polynomial Regression for Predicting Rice Prices in Lhokseumawe City

Jurnal Sisfokom
Rice is a strategic food commodity in Indonesia, and its price fluctuations significantly impact inflation, economic stability, and poverty levels. Accurate price prediction is, therefore, essential for effective policymaking.
Muhammad Iqbal, Rozzi Kesuma Dinata, Rizki Suwanda   +2 more
doaj   +1 more source

Comparison of Forecasting Performance of ARIMA LSTM and HYBRID Models for The Sales Volume Budget of a Manufacturing Enterprise

Istanbul Business Research, 2021
This study aims to create a monthly sales quantity budget by making use of the previous income data of an enterprise operating within the construction sector, which is considered the locomotive of the economy.
Ayşe Soy Temür, Şule Yıldız
doaj   +1 more source