Search Results - parallel prediction ((((using algorithm) OR (mining algorithm))) OR (learning algorithm))*
Search alternatives:
- parallel prediction »
- learning algorithm »
- mining algorithm »
- using algorithm »
-
1
Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Our results indicate that gene expression profiles combined with carefully chosen learning algorithms can predict patient survival for certain diseases.…”
Get full text
Get full text
Get full text
Proceeding Paper -
2
The forecasting of poverty using the ensemble learning classification methods
Published 2023“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
Get full text
Get full text
Get full text
Article -
3
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…New Iterative Alternating Group Explicit (NAGE) is a powerful parallel numerical algorithm for multidimensional temperature prediction. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
4
Leveraging data lake architecture for predicting academic student performance
Published 2024“…In addition to forecasting the student performance, appropriate machine learning algorithms such as Support Vector Classifier, Naive Bayes, and Decision Trees are used to build prediction models by using the data lake's scalability and parallel processing capabilities. …”
Get full text
Get full text
Get full text
Article -
5
Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia
Published 2024“…Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. …”
Article -
6
Protein secondary structure prediction from amino acid sequences using a neural network classifier based on the Dempster-Shafer theory
Published 2003“…As a result, this research extends the initial work by examining its potential improvements and applicability in a new real world task such as the protein secondary structure prediction. In order to reduce the computational demand when training with large data of proteins, an interface was developed using the data parallel approach to parallelize the training phase of the classifier and other accompanying methods such as data clustering algorithms. …”
Get full text
Get full text
Thesis -
7
-
8
Adaptive genetic algorithm to improve negotiation process by agents e-commerce
Published 2011“…The proposed negotiation algorithm employs Bayesian learning and similarity functions in order to predict opponent agent’s type and preferences. …”
Get full text
Get full text
Thesis -
9
Extreme Learning Machines: A new approach for prediction of reference evapotranspiration
Published 2023Article -
10
Random sampling method of large-scale graph data classification
Published 2024“…Since the data blocks in this model are much smaller than the entire data set, it is more efficient to analyze them on a standalone small machine, and multiple data blocks can be analyzed on multiple nodes of the cluster in parallel. Finally, we classified the graphs of data blocks using the SVM algorithm. …”
Get full text
Get full text
Get full text
Article -
11
Communication and computational cost on parallel algorithm of PDE elliptic type
Published 2009“…The parallel algorithms of 2-dimensional Partial Differential Equation (PDE) elliptic type for the prediction will be executed using distributed memory of heterogeneous cluster platform on LINUX-based environment. …”
Get full text
Get full text
Book Section -
12
-
13
Super resolution imaging using modified lanr based on separable filtering
Published 2019“…Super resolution is then achieved using the regularized patch representation (projection matrix) learned to predict the high resolution image features. …”
Get full text
Get full text
Thesis -
14
Tumor growth prediction using parallel computing: numerical solutions based on multi-dimensional partial differential equation (PDE)
Published 2010“…The tools of partial different equations via multi-dimensional parabolic types are emphases as the computational engine for the future prediction of the cell growth. This study focuses on the implementation of parallel algorithm for the simulation of tumor growth using two dimensional Helmholtz’s wave equation on a distributed parallel computing system. …”
Get full text
Get full text
Get full text
Get full text
Book -
15
Parallel Implementation of Two Level Barotropic Models Applied to the Weather Prediction Problem
Published 2004“…Forecasting model for short range weather prediction that is used here is the two level Barotropic models. …”
Get full text
Get full text
Thesis -
16
Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…In our laboratory, the coupling of a neural network (NN) and reinforcement learning (RL) is considered useful because of its autonomous, parallel and flexible learning ability. …”
Get full text
Get full text
Thesis -
17
Acquisition of context-based word recognition by reinforcement learning using a recurrent neural network
Published 2012“…In our laboratory, the coupling of a neural network (NN) and reinforcement learning (RL) is considered useful because of its autonomous, parallel and flexible learning ability. …”
Get full text
Get full text
Undergraduates Project Papers -
18
Parallel Kalman filter-based multi-human tracking in surveillance video
Published 2014“…A Kalman filter is a recursive algorithm which predict the state variables and further uses the observed data to correct the predicted value. …”
Get full text
Get full text
Conference or Workshop Item -
19
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
Get full text
Get full text
Thesis -
20
An integrated priority-based cell attenuation model for dynamic cell sizing
Published 2012“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
Get full text
Get full text
Get full text
Article