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1
Forecasting model based on LSSVM and ABC for natural resource commodity
Published 2013“…Reliable forecast of the price of natural resource commodity is of interest for a wide range of applications.This includes generating macroeconomic projections and in assessing macroeconomic risks.Various approaches have been introduced in developing the required forecasting models.In this paper, a forecasting model based on an optimized Least Squares Support Vector Machine is proposed.The determination of hyper-parameters is performed using a nature inspired algorithm, Artificial Bee Colony.The proposed forecasting model is realized is gold price forecasting.The undertaken experiments showed that the prediction accuracy and Mean Absolute Percentage Error produced by the proposed model is better compared on the one produced using Least Squares Support Vector Machine as an individual.…”
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2
Time series forecasting of energy commodity using grey wolf optimizer
Published 2015“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
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3
Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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4
Data normalization techniques in swarm-based forecasting models for energy commodity spot price
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5
Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer
Published 2015“…Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). …”
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6
Design and development of hybrid integrated thermal aware job scheduling on computational grid environment
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7
Ensemble deep learning approach for apple fruitlet detection from digital images
Published 2024“…Agriculture commodities are commodities that have a high economic worth and the potential to be developed further. …”
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8
A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2022“…As a result, a new grading system based on artificial algorithms, namely K-Nearest Neighbor algorithms, was established. …”
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A comprehensive review of crop yield prediction using machine learning approaches with special emphasis on palm oil yield prediction
Published 2021“…Due to this developing significance of crop yield prediction, this article provides an exhaustive review on the use of machine learning algorithms to predict crop yield with special emphasis on palm oil yield prediction. …”
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10
Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods
Published 2024“…Referring to the results of this study, the system can provide planting time recommendations based on prediction of rainfall, air temperature, and wind speed parameters through a web-based platform. …”
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Predictive Analytics for Crude Oil Price Using RNN-LSTM Neural Network
Published 2020“…This study aims to certify the capability of a prediction model built based on the RNN-LSTM network to predict the future price of crude oil. …”
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12
An embedded database design and implementation of a parallel IEEE XTS storage encryption for mobile devices
Published 2017“…To ensure higher security level, the developed system is implemented using the NIST-certified XTS-AES block encryption algorithm. …”
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13
Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models
Published 2019“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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14
Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…The fast growth of oil palm has resulted in its development as a strategic global commodity. Oil palm creates export revenues and strengthens the economies of numerous nations, especially Indonesia and Malaysia. …”
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