Search Results - (( property distribution function algorithm ) OR ( based evaluation method algorithm ))
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…The rest sets of experiments carried out to evaluate the proposed algorithms. Precisely, the second set revealed that the proposed genetic medoid based algorithms with both DB and VRC fitness functions produced more accurate results compared with the genetic means based algorithms in terms of the Fscore. …”
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2
A Novel Approach Of Groebner Bases Computation For Safety Analysis Of Distributed Discrete Controllers
Published 2019“…In this research, our main objective is to generate a new model checking computation method based on Groebner bases algorithm for safety property analysis of distributed discrete controllers. …”
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Technical Report -
3
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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4
On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…The statistical properties of the TTHPLD model, which are based on moments, order statistics, hazard rate functions, reliability functions, and Renyi entropy, have been studied. …”
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Article -
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Geometric feature descriptor and dissimilarity-based registration of remotely sensed imagery
Published 2024journal::journal article -
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Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The knowledge is combined using a novel empirical Bayes type approach, where the prior distribution for the model parameter is constructed based on the external knowledge, and the likelihood is calculated based on the internal knowledge. …”
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UMK Etheses -
8
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…The first part of the study derives the explicit solutions of the moment properties (mean, variance, skewness and kurtosis) of the distributions together with their respective autocovariance and autocorrelation functions, up to the ith order. …”
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10
Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…Thus, this research aims to standardize and weigh the evaluation criteria of MaOO competitive algorithms base on fuzzy Delphi and new fuzzy-weighted zero-inconsistency (FWZIC) methods. …”
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11
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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12
Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…Some of the theoretical properties of the distributions are derived and the distributions' characteristics are studied. …”
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14
Sudoku Generator based on hybrid algorithm / Faridah Abdul Rahman
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15
Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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Article -
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
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Multi-base number representation in application to scalar multiplication and pairing computation
Published 2011“…Multi-bases number representation is used to construct new versions of Miller’s algorithm. …”
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18
Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…In this study an inverse procedure algorithm is proposed in the time domain to evaluate lightning return stroke current based on measured electromagnetic fields at an observation point. …”
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The algorithm was written by using MATLAB software. The local tone mapping method is based on the modified contrast limited adaptive histogram equalization (CLAHE) method. …”
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20
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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