Search Results - (( variable making model algorithm ) OR ( java application customization algorithm ))

Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Model built resulted in variables importance’s ranking and subsequently, prediction can be made. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…s orthogonal array is used as a variable selection approach in optimizing the predictive model. …”

Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

“…In the oil palm industry, modelling and selecting variables play a crucial role in apprehending different issues, i.e. decision making. …”
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Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines by Noroziroshan, Alireza

“…Due to NP-hard nature of sequencing problem in mixed model assembly line, a genetic algorithm is applied to cope with problem complexity and obtain a near optimal solution in a reasonable amount of time. …”
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Using machine learning algorithms to develop a clinical 2 decision-making tool for COVID-19 inpatients by Vepa, Abhinav, Saleem, Amer, Rakhshan, Kambiz, Daneshkhah, Alireza

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Comparison on queuing performance measures on customer’s flow using Queuing Theory Model and DSW Algorithm / Muhammad Izuanudin Azmi ... [et al.] by Azmi, Muhammad Izuanudin, Azizul, Muhamad Aiman Zulhaikal, Abd Razak, Nurul Aisyah, Mohd Zaki, Noor Hidayah

“…In a multi-server fuzzy queuing model, the approximate technique DSW algorithm is employed to describe a membership function regarding the performance measures (Thamotharan,2016). …”
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Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

“…Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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A hybrid model of system dynamics and genetic algorithm to increase crude palm oil production in Malaysia by Mohd Zabid, M. Faeid

“…Furthermore, the hybrid model provides the ability of identifying the policy variables related to the objective function at any specific time line. …”
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An Intelligent Process Model for Manufacturing System Optimization by Ho , Kok Hoe, Kanesan , Muthusamy, Harikrishnan , Kanthen

“…The mathematical theorem is modeled with Industrial Engineering (IE) variables into spreadsheet to perform intelligent decision making. …”
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Development of fault detection, diagnosis and control system identification using multivariate statistical process control (MSPC) by Ibrahim, Kamarul 'Asri, Ahmad, Arshad, Ali, Mohamad Wijayanuddin, Mak, Weng Yee

“…In this research work, an FDD algorithm is developed using MSPC and correlation coefficients between process variables. …”
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Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

“…While quantitative technique is based on statistical concepts and requires large amount of data in order to formulate the mathematical models.This technique can be classified into projective and causal technique.The projective technique (or univariate modelling) just involve one variable while the causal technique (or econometric modelling) suitable for multi-variables.Since forecasting involves uncertainty, several methods need to be executed on one set of time series data in order to produce accurate forecast.Hence, usually in practice forecaster need to use several softwares to obtain the forecast values.If this practice can be transformed into algorithm (well-defined rules for solving a problem) and then the algorithm can be transformed into a computer program, less time will be needed to compute the forecast values where in business world time is money.In this study, we focused on algorithm development for univariate forecasting techniques only and will expand towards econometric modelling in the future.Two set of simulated data (yearly and non-yearly) and several univariate forecasting techniques (i.e. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan , Yin Keong

“…The solution obtained from the LB-MILP model, i.e., the decision variables (binary variables), was used to obtain a feasible solution for model UB-NLP. …”
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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

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A parallel genetic algorithm-based TSK-Fuzzy system for dynamic car-following modeling by Purnomo, Muhammad Ridwan Andi, Abdul Wahab, Dzuraidah, Hassan, Azmi, Rahmat, Riza Atiq

“…This paper presents the application of Parallel Genetic Algorithm (PGA)-based Takagi Sugeno Kang (TSK)-Fuzzy approach for dynamic car-following modeling in the traffic simulation software. …”
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Enhancing obfuscation technique for protecting source code against software reverse engineering by Mahfoudh, Asma

“…The proposed technique can be enhanced in the future to protect games applications and mobile applications that are developed by java; it can improve the software development industry. …”
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA by Zahari, Taha, Farzad, Tahriri, Siti Zawiah, Md Dawal

“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

“…Four methodologies are to make four different CM models to solve MRO problems. …”
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Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm by Hannan M.A., Akhtar M., Begum R.A., Basri H., Hussain A., Scavino E.

Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…The significant factors and their relationships are identified through a modelling approach. A modeling approach is developed which focuses on the phases in the model-building procedures, effects of interactions variables on the model, minimizing the effects of multicollinearity on the variables and recommending remedial techniques to overcome them, identification of the significant variables by removing insignificant variables, selecting the best model using the eight selection criteria (8SCs), and finally using the residual analysis to validate the chosen best model. …”
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