Search Results - (( probable distribution issues algorithm ) OR ( data distribution methods algorithm ))

Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching by Low, Yeh Ching

“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
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Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment by Mohd Ali, Fazlina

“…In order to store these huge volumes with heterogenous data categories, cloud computing became the mainstream solution to provide multiple services to keep safe, process and distribute the data. …”
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Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…The proposed BANN model achieved the best training accuracies of (95%) and best prediction accuracies of (92%) based on testing data compared to other employed methods. …”
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The Distribution Network Reconfiguration Improved Performance of Genetic Algorithm Considering Power Losses and Voltage Profile by Shamsuddin, Nur Hazahsha, Omar, Nu Farhana, Sulaima, Mohamad Fani, Jaafar, Hazriq Izzuan, Abdul Kadir, Aida Fazliana

“…This paper proposes heuristic Genetic Algorithm known as SIGA (Selection Improvement in Genetic Algorithm) in consideration of genetic operator probabilities likewise the progression of switch adjustment in Distribution Network Reconfiguration (DNR) while satisfying the parameters constraints. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. The higher level priority agreements give a higher or equal probability than the lower level, this technique is perfect at a core router by scheduling algorithm. …”
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Spatial analysis of infant mortality in Peninsular Malaysia over three decades using mixture models by Nuzlinda Abdul Rahman, Abdul Aziz Jemain

“…However, the issue concerned is whether the improvement is uniformly distributed throughout the country. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing by Goh, Kwang Yi

“…The idea was to change the probability distribution over the sequence space. Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

“…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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Network reconfiguration and control for loss reduction using genetic algorithm by Jawad, Mohamed Hassan Izzaldeen

“…All the data for 18-bus system test are taken from previous work, and all the data for 49-bus system test are taken from an existing Iraqi distribution network. …”
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Optimal search algorithm in a big database using interpolation–extrapolation method by Kabir, M. Nomani, Alginahi, Yasser M., Ali, J., Abdel-Raheem, E.

“…Search using traditional binary-search algorithm can be accelerated by employing an interpolation search technique when the data is regularly distributed. …”
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Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…In this study, three imputation methods are considered namely expectation-maximization (EM) algorithm and data augmentation (DA) algorithm. …”
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Three phase fault algorithm in distribution system by using database approach and impedance based method by Shamsudin, N.H., Latiff, A.A., Abas, N., Mokhlis, Hazlie, Awalin, L.J.

“…The comparison is made through proposed algorithm with actual data acquired from the utility board. …”
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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Deadline-aware heuristics for reliability optimization in ubiquitous mobile edge computing by Zaman, S.K.U., Maqsood, T., Ramzan, A., Rehman, F., Mustafa, S., Shuja, J.

“…We consider the latency and offloading failure probability as performance evaluation parameters. The simulation results reveal that the proposed Deadline-aware Heuristic Algorithm (DHA) achieves a remarkable total latency of 12.67Â ms, coupled with a mere 0.095 probability of offloading failure. …”
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Improving the exploration strategy of an automated android GUI testing tool based on the Q-Learning algorithm by selecting potential actions by Goh, Kwang Yi, Baharom, Salmi, Din, Jamilah

“…The idea was to change the probability distribution over the sequence space. Instead of making purely random selections, the least frequently executed action is selected so that the GUI can be further explored. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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Solving economic load dispatch problem using genetic algorithm method / Norliza Kamarulzaman by Kamarulzaman, Norliza

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Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…In general, both methods are performing well for analyzing extreme model but numerical results show that MTM method performs slightly better than MH method in terms of efficiency and convergency to the stationary distribution. …”
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