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  1. 1
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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  2. 2
    Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction

    Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction by Ghazvinian H., Mousavi S.-F., Karami H., Farzin S., Ehteram M., Hossain M.S., Fai C.M., Hashim H.B., Singh V.P., Ros F.C., Ahmed A.N., Afan H.A., Lai S.H., El-Shafie A.

    Published 2023
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  3. 3
    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming

    Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Sebastian, P., Hamid, N.H.B., Ahmed, E.F.

    Published 2022
    “…Thus, related surveillance planning methods optimize the placement of visual sensors based on equally significance grids by not limiting to demand of coverage. …”
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  4. 4
    Performance optimization method in OFDM based on majorization and minimization technique

    Performance optimization method in OFDM based on majorization and minimization technique by Al-Saadi, Alaa Abdullah, Latip, Rohaya, Muhammed, Abdullah

    Published 2019
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  5. 5
    Use of AR Block Processing for Estimating the State Variables of Power System

    Use of AR Block Processing for Estimating the State Variables of Power System by Mohd Nor, Nursyarizal, Jegatheesan, Ramiah, Perumal, Nallagownden

    Published 2008
    “…Samples of the local utility network for 103-bus parameter are collected and simulated using Burg and Modified Covariance algorithm to estimate the state variables. Simulation results to support the proposed method are also presented and compared with WLS method.…”
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  6. 6
    Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions

    Modeling and analysis of the impact of information and communication technology on household consumption expenditure in different regions by Fan, Chaozhi, Law, Siong Hook, Ibrahim, Saifuzzaman, Naseem, N. A. M.

    Published 2022
    “…Based on the panel data of cities and towns in China, by using the generalized estimation method of a dynamic panel, through the construction of regional household consumption expenditure evaluation models, optimize the impact evaluation algorithm of household consumption expenditure in different regions, standardize critic indicators, and build the impact modeling of household consumption expenditure in combination with relevant algorithms such as the Engel coefficient. …”
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  7. 7
    Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation

    Optimization of Motion Compensated Block-Based DCT Video Compression for Software Implementation by Chen, Soong Der

    Published 2000
    “…Then, various optimized algorithms for the two core processes in the compression, DCT and motion estimation, were reviewed and analyzed. …”
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  8. 8
    Implementation of Symmetric Rank-One Methods for Unconstrained Optimization

    Implementation of Symmetric Rank-One Methods for Unconstrained Optimization by Khiyaban, Farzin Modarres

    Published 2010
    “…We then examine a new scaled memoryless SR1 method based on modied secant equation for solving large-scale unconstrained optimization problems. …”
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  9. 9
    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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  10. 10
    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian

    Solving power system state estimation using orthogonal decomposition algorithm / Tey Siew Kian by Tey, Siew Kian

    Published 2009
    “…By using real time measurements and historical data base, power system state estimator detects errors in measurements and the data base; and calculates an optimal estimate of the system state vector of the bus voltage magnitudes and angles. …”
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  11. 11
    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques

    Automated density and growth estimation in precision aquaculture systems for prawn cultivation using computer vision techniques by Chong, Xiao Wei

    Published 2024
    “…By employing the state-of-the-art You Only Look Once (YOLO) v7 object detection algorithm, the project aims to develop a system capable of accurately detecting and classifying prawns based on their growth stages. …”
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  12. 12
    Using genetic algorithms to optimise land use suitability

    Using genetic algorithms to optimise land use suitability by Pormanafi, Saeid

    Published 2012
    “…The Erosion Potential Method (EPM) used in erosion estimation and sediment yield of the study. …”
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  13. 13
    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. …”
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  14. 14
    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images

    Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

    Published 2016
    “…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. …”
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  15. 15
    On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee

    On-orbit spatial image characterisation and restoration based on stochastic characteristic targets / Wong Soo Mee by Wong , Soo Mee

    Published 2021
    “…In continuation of the first framework, the proposed MTF measurement algorithms are evaluated experimentally as a blur kernel estimation method for spatially varying and invariant blur removal. …”
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  16. 16
    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani

    Power prediction using the wind turbine power curve and data-driven approaches / Ehsan Taslimi Renani by Ehsan Taslimi , Renani

    Published 2018
    “…To evaluate the performance of the Weibull parameters’ estimator methods, two sets of data are considered, one based on simulated data with different random variable size and the other based on actual data collected from a wind farm in Iran. …”
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  17. 17
    Improvement of an integrated global positioning system and inertial navigation system for land navigation application

    Improvement of an integrated global positioning system and inertial navigation system for land navigation application by Hasan, Ahmed Mudheher

    Published 2012
    “…This work also presents a new method for de-noising the GPS and INS data and estimate the INS error using wavelet multi-resolution analysis algorithm (WMRA) based particle swarm optimization (PSO) with a well designed structure appropriate for practical and real time implementations due to its very short optimizing time and elevated accuracy. …”
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  18. 18
    Qualitative and quantitative accuracy evaluation of 18f-fdg PET/CT with TOF and NON-TOF system on beta value in BPL reconstruction

    Qualitative and quantitative accuracy evaluation of 18f-fdg PET/CT with TOF and NON-TOF system on beta value in BPL reconstruction by Hui, Ng Suk

    Published 2024
    “…Penalised likelihood estimation algorithms, on the other hand, allow for an effective convergence that improves image quality by enhancing contrast and reducing noise. …”
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    Monograph
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  19. 19
    Decentralized time domain muting for interference mitigation in LTE-advanced heterogeneous networks

    Decentralized time domain muting for interference mitigation in LTE-advanced heterogeneous networks by Gadam, Mohammed Aliyu, Ahmed, Maryam Abdulazeez, Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

    Published 2015
    “…System level simulation was conducted to validate the throughput performances and the MeNBs- PeNBs resource trade-offs of the proposed method. Compared to the baseline (centralized) approach, the proposed decentralized TDM algorithm exhibited optimal throughput performance and adapted to the change in CRE bias with better trade-offs.…”
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  20. 20
    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model

    State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model by Dickson Neoh Tze How, Dr.

    Published 2023
    “…The Transformer model with transferred weights outperformed models trained from scratch using supervised learning. To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
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