Search Results - (( data selection method algorithm ) OR ( variable detection sensor algorithm ))
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1
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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2
A study on advanced statistical analysis for network anomaly detection
Published 2005“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Monograph -
3
Fault detection and diagnosis using correlation coefficients
Published 2005“…Normal Correlation (NC), Principal Component Analysis (PCA) and Partial Correlation Analysis (PCorrA) are used to develop the correlation coefficients between the selected key process variables with the quality variables of interest in the process from the NOC data. …”
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4
Observer-based fault detection with fuzzy variable gains and its application to industrial servo system
Published 2020“…Also, a scoring algorithm has been implemented, to evaluate the classification ability of the algorithm and the early fault detection ability. …”
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5
Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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6
Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach
Published 2004“…This paper examines use of multi-sensor remote sensing approach for deforestation detection in the tropics. …”
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7
Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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8
Cluster head selection using fuzzy logic and chaotic based genetic algorithm in wireless sensor network
Published 2013“…Wireless sensor networks (WSNs) are composed of hundreds or thousands of sensor nodes in order to detect and transmit information from its surrounding environment. …”
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9
Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory
Published 2015“…State observers are then implemented as the fault detection method in which the discrepancies between the measured values by the sensors and the values of the model are expressed as residuals. …”
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10
DESIGN OF SMART TRAFFIC LIGHT SYSTEM BASED ON INTERNET OF THINGS
Published 2018“…Density of the traffic is calculated by the algorithm that have various variables. This project will use Arduino as it microcontroller and the ultrasonic is used to detect the congestion. …”
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Final Year Project Report / IMRAD -
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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12
Faulty sensor detection mechanism using multi-variate sensors in IoT
Published 2019“…Because of this, we proposed two methods for Faulty Sensor Detection and Identification mechanism based on multi-variate sensors for Smart Parking System and smart agriculture. …”
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13
Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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14
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
15
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…Among the most serious limitations facing the success of future consumer gas identification systems are the drift problem and the real-time detection due to the slow response of most of todays gas sensors. …”
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16
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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17
Obstacle avoidance robot using sonar sensor (OARuS)
Published 2008“…For this operation, if sensor detect obstacle, robot will move direction no restriction to reach to last post.…”
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Learning Object -
18
Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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Conference or Workshop Item -
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Case Slicing Technique for Feature Selection
Published 2004“…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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20
Attribute related methods for improvement of ID3 Algorithm in classification of data: A review
Published 2020“…Results of the reviewed techniques show that attribute selection methods capable to resolve the limitations in ID3 algorithm and increase the performance of the method. …”
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