Search Results - (( location estimation method algorithm ) OR ( using vectorization learning algorithm ))

Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Yusuf, Badronnisa

“…The aim of this study was to produce a land cover map on the distribution of oil palm plantations on three districts located in Selangor. Landsat 8 images of resolutions 15 x 15 m were used and classified via machine learning and non-machine learning algorithms. …”
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Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms by Lai V., Ahmed A.N., Malek M.A., Afan H.A., Ibrahim R.K., El-Shafie A., El-Shafie A.

Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. …”

Wi-Fi received signal strength-based hyperbolic location estimation for indoor positioning systems by Narzullaev, Anvar, Selamat, Mohd Hasan, Sharif, Khaironi Yatim, Muminov, Zahriddin

“…The proposed algorithm combines signal sampling and hyperbolic location estimation techniques to estimate the location of mobile users. …”
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Enhanced location and positioning in wimax networks with virtual mimo base station by Othman, Muhammad Hakim

“…The developed algorithm includes the effect of the geometric dilution of precision (GDOP) to assist with the location estimation accuracy. …”
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Support directional shifting vector: A direction based machine learning classifier by Kowsher, Md., Hossen, Imran, Tahabilder, Anik, Prottasha, Nusrat Jahan, Habib, Kaiser, Zafril Rizal, M Azmi

“…In this article, we have focused on developing a model of angular nature that performs supervised classification. Here, we have used two shifting vectors named Support Direction Vector (SDV) and Support Origin Vector (SOV) to form a linear function. …”
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Particle filter approach for estimating indoor mobile user location using IEEE 802.11 signals (F1090) by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Md. Latiff , Nurul Hidayati

“…This creates problem in tracking user location indoor. Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. …”
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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms by Bundak, Caceja Elyca

“…Therefore, both algorithms need more improvement in future works to achieve a better estimation location.…”
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Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Therefore, this study investigates the capability of various machine learning algorithms in predicting the power production of a reservoir located in China using data from 1979 to 2016. …”

Wi-Fi received signal strength-based hyperbolic location estimation for indoor positioning systems by Narzullaev A., Selamat M.H., Sharif K.Y., Muminov Z.

Utilising MIMO for Location and Positioning in IMT -Advanced Systems by Awang Md Isa, Azmi

“…The results of our simulation demonstrate that the proposed algorithm is significantly more effective in location accuracy than the conventional technique (LLS algorithm) and MIMO antenna configurations can achieve high accuracy for location estimation which meets the Federal Communications Commission (FCC) requirements.…”
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Particle filter approach for tracking indoor user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Raman, Shakiratul Husna, Latiff , N. H. M.

“…This creates problem in tracking user location indoor. Moreover, the use of light estimation algorithms such as fingerprinting, ranking algorithm, Weighted Centroid method, k-Nearest Neighbour, did not give a good tracking result. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems by Mohammad Khamees Khaleel, Alsajri

“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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An improved algorithm for iris classification by using support vector machine and binary random machine learning by Kamarulzalis, Ahmad Haadzal

“…In machine learning, there are three type of learning branch that can used in classification procedures for data mining. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. All of the algorithms are later combined to provide device location estimation for multi-floor environment. …”
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Assessment and Evaluation of Different Machine Learning Algorithms for Predicting Student Performance by Alsariera Y.A., Baashar Y., Alkawsi G., Mustafa A., Alkahtani A.A., Ali N.

Short circuit power based fault location algorithm in distribution networks by Farzan, Payam, Izadi, Mahdi, Gomes, Chandima, Ab Kadir, Mohd Zainal Abidin, Hesamian, Mohammad Hesam, Mohd Radzi, Mohd Amran

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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

k- Nearest Neighbor Algorithm For Improving Accuracy In Clutter Based Location Estimation Of Wireless Nodes by Muhammad Mansoor Alam, Mazliham Mohd Su'ud, Patrice Boursier, Shahrulniza Musa

“…This research is focusing on the precise location estimation of mobile node by using k - nearest neighbor algorithm (k-NN). …”