Search Results - (( data application using algorithm ) OR ( based verification mining algorithm ))
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)
Published 2023“…The PNDT consists of five components: agent's belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent's belief base with new normative protocol. …”
Short Survey -
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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Thesis -
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Development and implementation of a technique for norms-adaptable agents in open multi-agent communities
Published 2023“…Computer science; Systems science; Agent based simulation; Mining algorithms; Multi-agent community; nocv1; Normative agents; norms deatetcin; Norms detections; Third parties; Verification process; Multi agent systems…”
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Development Of Analytical Solution For Thermo-Mechanical Stresses Of Multilayered Pressure Vessel Based On Recursive Algorithm
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Final Year Project / Dissertation / Thesis -
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Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)
Published 2013“…The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…To avoid such overheads many techniques have been used, however in this thesis stream-based data processing model is used in which data is processed in the form of continuous instances of data items. …”
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Thesis -
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…Exploring the dataset features through the application of clustering algorithms is a viable means by which the conceptual description of such data can be revealed for better understanding, grouping and decision making. …”
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Enhancing Secure Sockets Layer Bulk Data Trnsfer Phase Performance With Parallel Cryptography Algorithm
Published 2007“…The proposed algorithm performs the encryption of the data and the calculation of the MAC in parallel. …”
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Thesis -
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Two objectives big data task scheduling using swarm intelligence in cloud computing
Published 2016“…The proposed method is evaluated using CloudSim and big data applications are used as sample of applications. …”
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Data discovery algorithm for scientific data grid environment
Published 2005“…By using this model, we study various discovery algorithms for locating data sets in a data grid system. …”
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Development of heuristic task scheduling algorithm in cloud computing
Published 2016“…As the immense growth of data have affected many organizations, there have been a need to adopt the cloud resources for processing big data applications which could cost highly by using traditional storage. …”
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Proceeding Paper -
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Spatial Clustering Algorithm for Time Series Rainfall Data Using X-Means Data Splitting
Published 2017“…Therefore, a clustering algorithm by introducing data transformation using X-means data splitting is proposed to investigate the spatial homogeneity of time series rainfall data. …”
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Image Encrytion Using Block Based Transformation Algorithm
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On density-based data streams clustering algorithms: A survey
Published 2017“…Recently, a lot of density-based clustering algorithms are extended for data streams. The main idea in these algorithms is using density-based methods in the clustering process and at the same time overcoming the constraints, which are put out by data stream’s nature. …”
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Conference or Workshop Item -
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An extended ID3 decision tree algorithm for spatial data
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Conference or Workshop Item -
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A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm has been around for over a century. While a rather simplistic and dated algorithm, it remains widely used and taught till this day. …”
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Final Year Project / Dissertation / Thesis
