Search Results - (( variable scale selection algorithm ) OR ( java adaptation optimization algorithm ))

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

Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

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Scaled Conjugate Gradient using strong Wolfe line search for portfolio selection / Nurfatihah Anizan by Anizan, Nurfatihah

“…Then, the scaled LAMR method is applied in portfolio selection problems, to determine the more suitable investment between CIMB Bank and Maybank. …”
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Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin by Mohamad Husnin, Shahirah Atikah

“…This indicated that the new scaled mBFGS algorithm performance is better than mBFGS algorithms.…”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…Classifier algorithms, namely the Support Vector Machine and K-Nearest Neighbours were used for benchmarking the performance of the Real-Valued Negative Selection Algorithms. …”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…The first set showed the efficiency and performance of the proposed composing techniques including: kmean++ algorithm for initialization, fitness scaling for fitness selection, the proposed split and merge mutation operator, and choosing the medoid instead of the mean as a centroid-selection schema. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

“…The next objective of the current study was to compare the performance of aforementioned algorithms with regard to predicting ability. The investigation of TEA-based esterquat cationic surfactant synthesis was started in a 50 ml scale. …”
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Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model by Salleh, Roselina, Shamsuddin, Siti Mariyam

“…The experiments have shown that the proposed model has outperformed other models with 99.5% forecasting accuracy for small-scale data and 99.84% for large-scale data. The empirical results obtained have proved that the GRANN_ARIMA model can provide a better alternative for time series forecasting due to its promising performance and capability in handling time series data for both small and large scale data.…”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour, Masoud, Ali, Zaipatimah, Othman, Muhammad Murtadha, Bo, Rui, Javadi, Mohammad Sadegh, Ridha, Hussein Mohammed, Alrifaey, Moath

“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”
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Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

“…Following the architecture selection phase, three sub-scenarios assumed from the number of hidden neurons; 15, 30 and 45 nodes were introduced into previous train-validate-test scenarios with chosen BR algorithm. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem by Ahmadipour M., Ali Z., Othman M.M., Bo R., Javadi M.S., Ridha H.M., Alrifaey M.

“…Simulation results are analyzed and compared with two popular and commonly used multi-objective-evolutionary algorithms namely, non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) on the problem. …”

Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING by M., Ramasamy, A., Shahid, H., Zabiri

“…Information Criteria have been reported to be used for the selection of relevant input variables and determination of optimal NN model structures. …”
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Artificial neural network for anomalies detection in distillation column by Taqvi, S.A., Tufa, L.D., Zabiri, H., Mahadzir, S., Shah Maulud, A., Uddin, F.

“…This research aims to use Artificial Neural Network to recognize anomalies in the distillation column. The pilot scale distillation column for the ethanol-water system is selected for the study. …”
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Scheduling the blended solution as industrial CO2 absorber in separation process by back-propagation artificial neural networks by Abdollahi, Yadollah, Sairi, Nor Asrina, Mohd Said, Suhana, Abouzari-lotf, Ebrahim, Zakaria, Azmi, Mohd Sabri, Mohd Faizul, Islam, Aminul, Alias, Yatimah

“…Therefore, none of the variables was negligible in the fabrication. Furthermore, the model predicted the optimum points of the variables to minimize the viscosity which was validated by further experiments. …”
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Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

“…In the PLSR model there is no variable selection procedure that able to remove the irrelevant wavelengths. …”
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Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro-climatic studies by Lawal, I.M., Bertram, D., White, C.J., Kutty, S.R.M., Hassan, I., Jagaba, A.H.

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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Apart from that, its tuning variables are tricky, as it requires intricate setting properties. …”
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