Search Results - (( data distribution means algorithm ) OR ( peer evaluation _ algorithm ))

An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…Overall, the k-means outperforms the Gaussian mixture distribution in selecting smaller feature subsets. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…One of the main issues in genetic k-means based algorithms is their sensitivity to outliers and unevenly distributed clusters due to the mean compromised computations. …”
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Replica Creation Algorithm for Data Grids by Madi, Mohammed Kamel

“…This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

“…Consequently, to handle these data, computer algorithms must adapt to their characteristics. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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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

“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data by Liang, Fei, Lu, Hezhi, Xi, Yuhang

“…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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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin, Ab Rahman, Hamim, Sakib Iqram

“…This study introduces an enhanced energy aware clustering approach that combines an improved K-Means algorithm with an adaptive distance threshold to optimize relay node selection and cluster formation. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

“…Location information is an integral part of wireless sensor networks, without location information, all received data will lose meaning. However, the current localization scheme is based on equipped GPS on every node, which is not cost-efficient and not suitable for large-scale wireless sensor networks and outdoor environments. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…The probabilistic values of PV generation and load models are employed as the input data to the load flow analysis for the radial distribution network. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Failing to address missing data can lead to inaccurate results during data analysis, as incomplete data sequences introduce biases and compromise the distribution of the synthesized data, and cause a negative impact on the decision-making process. …”
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Interferometric array planning using division algorithm for radio astronomy applications by Kiehbadroudinezhad, Shahideh

“…The algorithm is able to distribute the u-v plane more efficiently than GMRT with 49.77% overlapped samples. …”
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Land use evaluation for Kuala Selangor, Malaysia using remote sensing and GIS technologies by Nedal A Mohammad, Sharifah Mastura SA , Johari Mat Akhir

“…In evaluating landuse for sustainable use of natural resources several maps were taken as parameters and obtained from digital classification of SPOT 2005 data by means of supervised modes with maximum likelihood algorithm using necessary ground truth data. …”
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Predictive analysis of porous media–cooled photovoltaic panels using gradient-boosting machine learning models by Masalha, Ismail, Alahmer, Ali, Alsabagh, Abdel Salam, Badran, Omar, Masuri, Siti Ujila

“…Predictive performance was assessed using multiple metrics, including mean squared error, mean absolute error, coefficient of determination, Pearson correlation coefficient, Nash–Sutcliffe efficiency, Willmott's index of agreement, 95th percentile uncertainty, as well as Taylor diagrams and violin plots to evaluate residual distributions and uncertainty. …”
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Malay continuous speech recognition using continuous density hidden Markov model by Ting, Chee Ming

“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System by Hassan, Mahamat. I, Azween, Abdullah

“…In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-based service search and selection algorithm. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Failing to address missing data can lead to inaccurate results during data analysis, as incomplete data sequences introduce biases and compromise the distribution of the synthesized data. …”
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Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System by HASSAN, MAHAMAT ISSA

“…In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-qased service search and selection algorithm. …”
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