Search Results - (( java implication based algorithm ) OR ( parameters variation means algorithm ))

Hybrid Control of A Quadrotor System Carrying Suspended Payload With Parameter Variations by Amalin Aisya binti Mohd Awi

A proposed variable parameter control chart for monitoring the multivariate coefficient of variation by Chew, X. Y., Khoo, B. C., Khaw, K. W., Yeong, W. C. *, Chong, Z. L.

“…In certain processes where the process mean and variance are not independent of one another, the coefficient of variation (CV), which measures the ratio of the standard deviation to the mean, should be monitored. …”
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Model-based hybrid variational level set method applied to lung cancer detection by Jing, Wang, Liew, Siau-Chuin, Azian, Abd Aziz

“…The improved multi-scale mean filter approximates the image’s offset field, effectively reducing gray-scale inhomogeneity and eliminating the influence of scale parameter selection on segmentation. …”
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Metaheuristic approach for optimizing neural networks parameters in battery state of charge estimation by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Azlan Abdul, Abdul Aziz

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Monitoring the coefficient of variation using a variable sample size EWMA chart by Muhammad, Anis Nabila, Yeong, Wai Chung, Chong, Zhi Lin, Lim, Sok Li, Khoo, Michael Boon Chong

“…CV charts are attracting attention due to their usefulness in monitoring processes with an inconsistent mean and a standard deviation which changes with the mean. …”
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

“…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

“…The Back Propagation algorithm or its variation on Multilayered Feedforward Networks is widely used in many applications. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…In addition, ANFIS approach is implemented to predict the �436�45D of wind turbine blades for investigation of algorithms performance based on Coefficient Determination (R2) and Root Mean Square Error (RMSE). …”
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Renewable sources-based automatic load frequency control of interconnected systems using chaotic atom search optimization by Irudayaraj, Andrew Xavier Raj, Abdul Wahab, Noor Izzri, Premkumar, Manoharan, Mohd Radzi, Mohd Amran, Sulaiman, Nasri, Veerasamy, Veerapandiyan, Farade, Rizwan A., Islam, Mohammad Zohrul

“…Moreover, the sensitivity analysis is carried out by considering ±25 % variation in HPS parameters and the real-time applicability is tested with Malaysian meteorological data of solar radiation and wind speed variation. …”
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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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Design of super twisting algorithm for chattering suppression in machine tools by Chiew, Tsung Heng, Jamaludin, Zamberi, Bani Hashim, Ahmad Yusairi, Abdullah, Lokman, Rafan, Nur Aidawaty

“…This paper elaborates on the design and analysis of the super twisting algorithm with focus on optimizing the gain parameters. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…The statistical analysis value (mean) was taken from the parameter deviation index to see how much our proposed algorithm has improved. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The statistical error estimation exhibits a mean absolute error of 11.5, and root mean squared error of 0.87. …”
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Model-based hybrid variational level set method applied to object detection in grey scale images by Wang, Jing

“…This algorithm leverages an improved multi-scale mean filter to mitigate grayscale inhomogeneity while reducing the impact of scale parameter selection. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

“…The variation in different input parameters with adsorption was not increased or decreased synchronically. …”
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Gradient auto-tuned Takagi-Sugeno Fuzzy Forward control of a HVAC system using predicted mean vote index by Homod R.Z., Sahari K.S.M., Almurib H.A.F., Nagi F.H.

“…The proposed TSFF control method is tested in simulation taking into account practical variations such as thermal parameters of buildings, weather conditions and other indoor residential loads. …”

A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…After optimizing the proposed fuzzy model by means ofgenetic algorithm, the resulted planner produces shorter paths in shorter runtimes with limited variations in results of different runs of the planner. …”
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Nuclear Power Plant Burst Parameters Prediction During a Loss-of-Coolant Accident Using an Artificial Neural Network by Tumpa, P.P., Saiful Islam, M., May, Z., Khorshed Alam, M.

“…A neural network architecture of 2-15-15-15-3, which is a model of three hidden layers containing fifteen neurons in each layer is designed. The mean deviation of burst temperature, burst stress, and burst strain gained from the burst criteria is 1.15, 3.82, and 39.41, respectively, while these parameters are predicted by the proposed neural network includes mean deviations of 0.43, 1.57, and 3.85, respectively. …”
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Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors by Ehteram M., Afan H.A., Dianatikhah M., Ahmed A.N., Fai C.M., Hossain M.S., Allawi M.F., Elshafie A.