Search Results - (( variable extractions based algorithm ) OR ( probable distribution sensor algorithm ))

Energy Efficient LEACH (EE-LEACH) Routing Algorithm for Wireless Sensor Networks by Pillay, Kosheila Sundram

“…Therefore, this research work proposes an energy-efficient LEACH (EE-LEACH) algorithm to elect CHs based on residual energy, RSSI, and random probability to distribute the load evenly among the CHs. …”
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Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance by Akbari, M., Reza, A.W., Noordin, K.A., Dimyati, K., Manesh, M.R., Hindia, M.N.

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Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

“…For network clustering, the distribution of CH selection directly influences the networks lifetime. …”
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Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

“…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…In comparison, WISDM utilizes an accelerometer sensor embedded in Android smartphone. Meanwhile, PAMAP2 utilizes an accelerometer sensor equipped with three Inertial Measurement Unit (IMU) devices attached to three different placements. …”
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Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

“…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…In dealing with correlated variables, PCA was embedded in the proposed algorithm. …”
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Adaptive Step Size Based Hill-Climb Search Algorithm for MPPT Control of DFIG-WECS With Reduced Power Fluctuation and Improved Tracking Performance by Uddin M.N., Amin I.K.

Using a fatigue data editing approach for analysing cycle sequence effects in variable amplitude road loadings by S., Abdullah, J. C., Choi

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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

“…Therefore, this research has designed fuzzy learning algorithm that is able to classify fruits based on their shape and size features using Harumanis dataset. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. …”
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Multi road marking detection system for autonomous car using hybrid- based method by Shah, Khan Bahadur

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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…The textural features extracted are based on the first-order statistics and second-order statistics computed from grey level co-occurrence matrices (GLCM). …”
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EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS by ARSHAD, MUHAMMAD AYAZ ARSHAD

“…Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. …”
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Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphso... by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud

“…The proposed guaranteed convergence arithmetic optimization algorithm based on efficient modified third order Newton Raphson (GCAOAEmNR) method highlights important contributions to the literature in terms of methodology (explorer-exploiter phases) and objective function design. …”
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ECG-based driving fatigue detection using heart rate variability analysis with mutual information by Halomoan, Junartho, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya, Salman, Muhammad

“…For feature extraction, we employ heart rate fragmentation to extract non-linear features to analyze the driver’s cognitive status. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement by Abdul Rahman, Nor Farahaida

“…First, unified ADALINEs based fundamental component extraction algorithm is proposed for dual functionality. …”
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The framework of weighted subset-hood Mamdani fuzzy rule based system rule extraction (MFRBS-WSBA) for forecasting electricity load demand by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod

“…Fuzzy rules are very important elements that should be taken consideration seriously when applying any fuzzy system.This paper proposes the framework of Mamdani Fuzzy Rule-based System with Weighted Subset-hood Based Algorithm (MFRBS-WSBA) in the fuzzy rule extraction for electricity load demand forecasting.The framework consist of six main steps: (1) Data Collection and Selection; (2) Preprocessing Data; (3) Variables Selection; (4) Fuzzy Model; (5) Comparison with Other FIS and (6) Performance Evaluation. …”
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