Search Results - (( using vector sensor algorithm ) OR ( parameter classification using algorithm ))

Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Quantifying forest disturbance using LiDAR data and time series Landsat images / Syaza Rozali by Rozali, Syaza

“…Two fusion data are tested; 1) SpectralLandsat and 2) SpectralLandsat + HeightALS by Random Forest and Support Vector Machine classification algorithm. The result shows second fusion data having 1 meter Landsat resolution and Airborne LiDAR performed better classification using object-based segmentation and Random Forest classification, about 96% of the overall accuracy with 0.91 kappa index of aggreement. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Near-infrared technique for oil palm fruit grading system by Saeed, Osama Mohamed Ben

“…The developed system showed high classification results on accuracy of the maturity detection for the three types of oil palm fruits (nigrescens, virescens, and oleifera ) with rates of 95%, 99%, and 98 %, respectively, using the ANN-MLP classifier; rates of 96%, 99%, and 98 %, respectively, using the KNN classifier; and rates of 76%, 96%, and 94%,respectively, using SVM. …”
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Distance vector-hop range-free location algorithm for wireless sensor network by Zazali, Azyyati Adiah

“…Distance Vector-Hop (DV-Hop) algorithm has become the focus of studies for range-free localization algorithms. …”
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Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

“…This research explores path integration in mobile robot navigation and path optimization technique using vector calculus. A simulated robot in a simulated environment is used to test the algorithm that is to be developed. …”
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EEG signal complexity measurements to enhance BCI-based stroke patients' rehabilitation by Al-Qazzaz, Noor Kamal, Aldoori, Alaa A., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Mohammed, Ahmed Kazem, Mohyee, Mustafa Ibrahim

“…The dimensionality reduction algorithm, Laplacian Eigenmap (LE), was used to enhance the MI-based BCI classification performance. …”
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Flood Control Distance Vector Hop (FCDV-Hop) localization in wireless sensor networks by Zazali, Azyyati Adiah, Subramaniam, Shamala, Ahmad Zukarnain, Zuriati

“…Distance Vector-Hop (DV-Hop) localization is a distributed, hop by hop positioning algorithm. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Performance comparison of AODV, DSDV and EE-DSDV routing protocol algorithm for wireless sensor network by Norhizat, Mohd Taufiq, Ishak, Zulkifli, Sauti, Mohd Suhaimi, Jamaludin, Md Zaini

“…This paper describes a preliminary study on wireless sensor network (WSN) routing protocol algorithm with focus on energy saving strategy.Efficient energy saving and consumption will ensure the lifespan of the battery are prolonged and the delay of transmitting data will be within the acceptable range of 300 meter by 300 meter network size.The routing protocol Ad-hoc On Demand Distance Vector (AODV), Destination Sequence Distance Vector (DSDV) and Energy Efficient Destination Sequence Distance Vector (EE-DSDV) were used in the study to compare the performance of the network in terms of maximum delay, throughput receive as well as the remaining energy in the network.…”
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A distributed particle filtering approach for multiple acoustic source tracking using an acoustic vector sensor network by Zhong, X., Mohammadi, A., Premkumar, A.B., Asif, A.

“…Different centralized approaches such as least-squares (LS) and particle filtering (PF) algorithms have been developed to localize an acoustic source by using a distributed acoustic vector sensor (AVS) array. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi by Mazhar, Hussain Abbasi

“…Sensorless vector control technique using adaptive observer scheme is being used to control the performance of induction motor which is demonstrated by the help of matlab/simulink software; a suitable tool for vector control of AC motor. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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An enhanced distance vector-hop algorithm using new weighted location method for wireless sensor networks by Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz, Liu, Xinni, Kamarul Hawari, Ghazali

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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification by Nweke, Henry Friday, Teh, Ying Wah, Mujtaba, Ghulam, Alo, Uzoma Rita, Al-garadi, Mohammed Ali

“…To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. …”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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