Search Results - (( knowledge data normalization algorithm ) OR ( java adaptation optimization algorithm ))
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1
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
2
Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
Published 2021“…This research contributes to the world of health, where we classify the Electrocardiogram (ECG) data, so that it can classify abnormal and normal cardiac disorders using the Fuzzy Cognitive Map (FCM) algorithm.…”
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3
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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4
Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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5
An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms
Published 2015“…The hypothesis is that the tendency of normalization technique to simplify the data combined with the accuracy of the neighborhood models can improve the accuracy of the RS. …”
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6
An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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7
EEG Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…With controlled data types, healthy/normal, seizure and pre-seizure classes, tuning of algorithms for detection and classification applications can be attained. …”
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8
Unsupervised Anomaly Detection with Unlabeled Data Using Clustering
Published 2005“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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9
Eye Diagram Modeling Of High-Speed Channels Using Artificial Neural Networks With An Improved Adaptive Sampling Algorithm
Published 2019“…xxiii EYE DIAGRAM MODELING OF HIGH-SPEED CHANNELS USING ARTIFICIAL NEURAL NETWORKS WITH AN IMPROVED ADAPTIVE SAMPLING ALGORITHM ABSTRACT As data rates increase to the gigabit range and beyond, signal integrity (SI) analysis becomes increasingly difficult and time consuming process. …”
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10
What, how and when to use knowledge in neural network application
Published 2004“…; and When to use this knowledge? Knowledge is simply the weights that connect each neuron in neural networks. …”
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11
Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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12
Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The recent progress in computer storage technology have enable many organisations to collect and store a huge amount of data which is lead to growing demand for new techniques that can intelligently transform massive data into useful information and knowledge. …”
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13
Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).
Published 2007“…At the end of this paper, we presented an experimental result on a benchmark data to show how it could improve the fundamental ofACS algorithm.…”
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14
Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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15
Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…Presently, the classification accuracy of the assessment is proportional to the size of the data. Increasing the size of the data will make it more accurate. …”
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16
Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…Preprocessing removes noise from text data, normalizes sentiment word lists and undertakes temporal transformation. …”
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17
Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining
Published 2019“…A total of 600 x 23 features attributes comprising of leaf geometrical features, discriminant features and its derived quantities were collected by measurements, field observations and the tearing test performed using the Universal Testing Machine (UTM). The recorded data were screened on data normalization while the outliers were discarded prior to regression analysis aided by the Waikato Environment for Knowledge Analysis (WEKA) tool. …”
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18
Out-of-core simplification with appearance preservation for computer game applications
Published 2006“…However, powerful graphics workstation also unable to load or even generates the smooth rendering of these extremely large data. In this thesis, out-ofcore simplification algorithm is introduced to overcome the limitation of conventional technique. …”
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19
A fast knowledge-based plane reconstruction method from noisy 3D point cloud data
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20
Development of a diversified ensemble data summarization (DDS) tool for learning medical data in a multi relational environment
Published 2012“…Medical or scientific data are normally stored in relational databases in which data are stored in multiple tables. …”
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