Search Results - (( developing demand prediction algorithm ) OR ( java implication based algorithm ))

A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Chun T.S., Malek M.A., Ismail A.R.

“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…This study develops a hybrid model for the prediction of monthly water demand using the database of monthly urban water consumption in Melbourne, Australia. …”

A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

“…The significance of the selected input variable vectors is studied to analyze their effects on the prediction process. Another objective of the study is to develop and compare the prediction models for electrical energy demand of one day-ahead. …”
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Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm by Ting S.C., Ismail A.R., Malek M.A.

“…The novelty of this study is the development of a predictive SSTP model for effluent discharge adopting the human immune system. …”

Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant by Ting, Sie Chun, Abdul Malik, Marlinda, Ismail, Amelia Ritahani

“…The development of effluent removal prediction is crucial in providing a planning tool necessary for the future development and the construction of a septic sludge treatment plant (SSTP), especially in the developing countries. …”
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Development of effluent removal prediction model efficiency in septic sludge treatment plant through clonal selection algorithm by Sie Chun, Ting, Ismail , Amelia Ritahani, A. Malek, Marlinda

“…The novelty of this study is the development of a predictive SSTP model for effluent discharge adopting the human immune system. …”
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A review on the applications of PSO-based algorithm in demand side management: Challenges and opportunities by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Zulkafli, Nur Izyan, Mokhlis, Hazlie

“…The proposed PSO-based algorithm can optimize consumers’ consumption curves, reducing the peak demand and hence minimizing the electricity cost when integrated with the DR programs or EE measures. …”
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Formulation of model predictive control algorithm for nonlinear processes by Mohd. Yusof, Khairiyah, Hassim, Mimi Haryani, Tan, Sook Li, Ab. Rashid, Siti Rafidah

“…However, with faster computing technology, the industry is now demanding a tighter advanced control strategy. To fulfil all these objectives, Model Predictive Control (MPC), an optimal model based control algorithm is definitely the best choice among all the advanced control algorithms available to date. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…Because of this ability, they are extensively implemented in modern predictive model development. The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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Sales prediction of religious product and services of Mutawwif Haramain Travel & Tours using predictive analytics by Mohd Sabri, Nurul Ainin Qistina

“…This research develops a predictive model for sales prediction at Mutawwif Haramain Travel & Tours, utilizing machine learning algorithms, specifically Decision Tree, Random Forest, and Naive Bayes, to uncover patterns in customer behavior and seasonal demand. …”
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A smart food security monitoring and predicting algorithm for rice productivity in Southeast Asia by Chuan, Zun Liang, Tham, Ren Sheng, Abraham Lim, Bing Sern, David Lau, King Luen

“…Specifically, the methodology integrates Simple Linear Regression–Multivariable Linear Regression (SLR-MLR) into a unified predictive algorithm. By incorporating all four dimensions of food security: availability, accessibility, stability, and utilization, the proposed algorithms outperform conventional Artificial Intelligence (AI) predictive algorithms, offering superior accuracy and actionable insights. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…The verification results indicate that all the structural defects were predicted with high accuracy by the developed hybrid algorithm in cases of healthy and damaged structures. …”
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A novel approach based on machine learning and public engagement to predict water-scarcity risk in urban areas by Hanoon, Sadeq Khaleefah, Abdullah, Ahmad Fikri, M. Shafri, Helmi Z., Wayayok, Aimrun

“…The Water Evolution and Planning system was also used to predict unmet water demand as a relevant criterion, which was aggregated with other criteria. …”
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Predicting open space parking vacancies using machine learning by Lee, Wei Jun

“…Moreover, a PySimpleGUI was developed to provide an interactive parking vacancy prediction model graphic user interface (GUI).…”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…Thus, this research aim to develop a reverse migration prediction model based on machine learning. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

Predictive analytics for pacemaker medical instrument stock management of Transmedic Healthcare by Nawawi, Nafiz Danial

“…The research applies the CRISP-DM methodology, examining current stock processes, and then collecting and cleansing historical data to develop Always Better Control (ABC) for stock analysis and predictive models using classification and also making a comparison between three algorithms, which are Naive Bayes, Random Forest and Decision Tree. …”
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A New Hybrid Optimization Method Using Design Of Experiment Together With Artificial Neural Genetic Algorithm by Yahaya, Nor Zaiazmin

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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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