Results 81 to 90 of about 42,250 (218)

Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning

Food Bioengineering, EarlyView.
ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang, Shuangcheng Huang, Qingbo Lu, Xinyi Guo   +3 more
wiley   +1 more source

Consistance de la minimisation du risque empirique pour l'optimisation de l'erreur relative moyenne

, 2015
National audienceWe study in this paper the consequences of using the Mean Absolute Percentage Error (MAPE) as a measure of quality for regression models.
de Myttenaere, Arnaud, Le Grand, Bénédicte, Rossi, Fabrice   +2 more
core  

ESTIMASI BEBAN PUNCAK HARIAN BERDASARKAN KLUSTER TIPE HARI BERBASIS ALGORITMA HYBRID SWARM PARTICLE-ARTIFICIAL NEURAL NETWORK [PDF]

, 2014
Prediksi beban listrik jangka pendek merupakan salah satu perencanaan operasi sistem tenaga listrik yang memiliki peranan penting dalam hal mewujudkan operasi yang ekonomis.
Sofyan, Willy Wigia
core  

Forecasting New Employment Using Nonrepresentative Online Job Advertisements With an Application to the Italian and EU Labor Market

Journal of Forecasting, EarlyView.
ABSTRACT Using online job advertisement data improves the timeliness and granularity depth of analysis in the labor market in domains not covered by official data. Specifically, its variation over time may be used as an anticipator of official employment variations.
Pietro Giorgio Lovaglio, Mario Mezzanzanica   +1 more
wiley   +1 more source

Predictive modelling of marine fish landings in Malaysia [PDF]

, 2018
The fisheries sector plays an important role in the economy as a major source of food, employment and income in Malaysia. In this study, the future number of marine fish landings in Malaysia will be predicted.
Abdullah, Abdul Wahab, Azmi, Nur Amira, Mohd Robi, Nur Afifi Izzati, Rusiman, Mohd Saifullah, Sufahani, Suliadi Firdaus   +4 more
core   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source

Using Deep Learning Conditional Value‐at‐Risk Based Utility Function in Cryptocurrency Portfolio Optimisation

International Journal of Finance &Economics, EarlyView.
ABSTRACT One of the critical risks associated with cryptocurrency assets is the so‐called downside risk, or tail risk. Conditional Value‐at‐Risk (CVaR) is a measure of tail risks that is not normally considered in the construction of a cryptocurrency portfolio.
Xinran Huang, Linzhi Tan, Haozhe Su, Jeremy Eng‐Tuck Cheah   +3 more
wiley   +1 more source

Exploring PM2.5 and PM10 ML forecasting models: a comparative study in the UAE

Scientific Reports
Particulate Matters PM $$_{2.5}$$ and PM $$_{10}$$ present a major health and environmental concern in urban regions. This research compares machine learning and time series models, such as Decision Tree (DT), Random Forest (RF), Support Vector ...
Waad Abuouelezz, Nazar Ali, Zeyar Aung, Ahmed Altunaiji, Shaik Basheeruddin Shah, Derek Gliddon   +5 more
doaj   +1 more source

Wind speed prediction in some major cities in Africa using Linear Regression and Random Forest algorithms

Journal of Nigerian Society of Physical Sciences
Globally, wind energy if properly harnessed, could serve as a source of energy generation in Africa. This study compared the performance of two Machine Learning (ML) algorithms (Linear regression and Random Forest) in predicting wind speed in five major
Timothy Kayode Samson, Francis Olatunbosun Aweda   +1 more
doaj   +1 more source

Joint Estimation and Bandwidth Selection in Partially Parametric Models

Journal of Applied Econometrics, EarlyView.
ABSTRACT We propose a single‐step approach to estimating a model with both a known nonlinear parametric component and an unknown nonparametric component. We study the large sample behavior of a simultaneous optimization routine that estimates both the parameter vector of the parametric component and the bandwidth vector used to smooth the unknown ...
Daniel J. Henderson, Nadine McCloud, Christopher F. Parmeter   +2 more
wiley   +1 more source