Search Results - (( variable pricing model algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil by Jamil, Nur Syafiqah

“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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A NARX Neural Network Model to Predict One-Day Ahead Movement of the Stock Market Index of Malaysia by Dhafer A.H., Nor F.M., Hashim W., Shah N.R., Bin Khairi K.F., Alkawsi G.

Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…Electricity price forecasting is considered as one of prime factors for operation, planning and scheduling of price-setter market participants. …”
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Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction by Masrom, S., Baharun, N., Razi, N.F.M., Rahman, R.A., Abd Rahman, A.S.

“…Particle Swarm Optimization is a meta-heuristics algorithm widely used for optimization problems. This paper presents the research design and implementation of using Particle Swarm Optimization to automate the features selections in the machine learning models for Airbnb price prediction. …”
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Building fuzzy variance gamma option pricing models with jump levy process by Zhang, H., Watada, J.

“…Then, we adopts a Monte Carlo algorithm for numerical simulation, compares and analyses the variance gamma (VG) option pricing model through a simulation experiment, and determines the VG option pricing model and BS model pricing results. …”
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Building fuzzy variance gamma option pricing models with jump levy process by Zhang, H., Watada, J.

“…Then, we adopts a Monte Carlo algorithm for numerical simulation, compares and analyses the variance gamma (VG) option pricing model through a simulation experiment, and determines the VG option pricing model and BS model pricing results. …”
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

“…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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A comparative study between univariate and bivariate time series models for crude palm oil industry in peninsular Malaysia / Pauline Jin Wee Mah and Nur Nadhirah Nanyan by Wee Mah, Pauline Jin, Nanyan, Nur Nadhirah

“…However, ARIMA (0,1,0) appeared to be the best forecast model for price based on the MAE and MAPE values while ARFIMA (0, 0.08903, 0) emerged the best model based on the RMSE value. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

“…The research will provide an appropriate model in predicting the price of a green building which is beneficial to the government agencies and industry practices…”
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Development of a two-level trade credit model with shortage for deteriorating products using hybrid metaheuristic algorithm by Molamohamadi, Zohreh

“…A hybrid metaheuristic algorithm which combines Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm, is then developed to solve the established models. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

“…Results demonstrate that ARIMA outperforms the other models in all cases, accurately projecting the price variability within the actual price range. …”
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The Crop Price Prediction Using Machine Learning: Preliminary Stage by Ramya, T.K., Shreedhara N, Hegde, Mohd Norshahriel, Abd Rani

“…The back-end predictive model for this project is created utilizing machine learning algorithms. …”
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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Application of artificial neural network in share price forecasting / Zakiah Mustafa by Mustafa, Zakiah

“…In this projece,seven (7) input variables are chosen as the key factors for the changes of stock price. …”
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Indonesian Stock Price Prediction Using Neural Basis Expansion Analysis for Interpretable Time Series Method by Zein, Muhamad Harun, Yudistira, Novanto, Adikara, Putra Pandu

“…Therefore, a model is needed to predict future stock prices, one strategy for maximising investment profits. …”
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A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization by Jamal S., Pasupuleti J., Ekanayake J.

“…However, this process is affected by several factors, like load variability, market pricing, and the intermittent nature of Wind Turbines (WTs) and Photovoltaic (PV) systems. …”

Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques by Kayalvily, Tabianan, Denis, Arputharaj, Mohd Norshahriel, Abd Rani, Sarasvathi, Nahalingham

“…This study aims to predict the ratings of Google Play Store apps using decision trees for classification in machine learning algorithms. The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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