Search Results - (( using optimization method algorithm ) OR ( knowledge estimation using algorithm ))

The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

“…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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Application of genetic algorithm for fuzzy rules optimization on semi expert judgment automation using Pittsburg approach by Tan C.H., Yap K.S., Yap H.J.

“…Genetic algorithm is well-known of its best heuristic search method. …”

Multilevel optimization for dense motion estimation by Saaban, Azizan, Kalmoun, El Mostafa, Ibrahim, Haslinda, Ramli, Razamin, Omar, Zurni

“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. …”

Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

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

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm by Lipu M.S.H., Hannan M.A., Hussain A., Saad M.H.M., Ayob A., Muttaqi K.M.

Integration of knowledge-based seismic inversion and sedimentological investigations for heterogeneous reservoir by Shahbazi, A., Monfared, M.S., Thiruchelvam, V., Ka Fei, T., Babasafari, A.A.

“…The extracted rules and optimized number rules then would be used for rule-based porosity estimation. …”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

“…In conclusion, the proposed low-complexity iterative algorithm can be used to maximize the EE based on the maximum transmit power , where the noise power is less than the power of the received pilot sequence.…”
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Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm by Tan Boon Tat, Boon Tat

“…In particular, GA is being extensively used in the field of optimization. This paper discusses the utilization of GA in estimating the coefficients and exponents in developing the Nusselt Number correlation in two different heat exchanger geometries, with the aim to reduce the error incurred in predicting heat transfer coefficients and heat transfer rates. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…The main objective of this project is to investigate the applicability of Recursive Least Squares (RLS) for parameter estimation methods in assisted history matching. Currently not much attention is given for using RLS for history matching purposes. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…In this regards, a new method of Pico-satellite attitude control using Mamdani Fuzzy Logic Principles is introduced. …”
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Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems by Salh, Adeeb, Audah, Lukman, Abdullah, Qazwan, M. Shah, Nor Shahida, A. Hamzah, Shipun, Nordin, Shahilah, Farah, Nabil

“…This formulates the optimization problem of joint optimal antenna selection, transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massiveMIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm (LCA) for Newton’s methods and Lagrange multipliers. …”
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Robust techniques for linear regression with multicollinearity and outliers by Mohammed, Mohammed Abdulhussein

“…The ordinary least squares (OLS) method is the most commonly used method in multiple linear regression model due to its optimal properties and ease of computation. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…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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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal by Aymen Taher , Ahmed al-Ashwal

“…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

“…Obviously, selecting four muscles to attain a full joint moment and motion is not sufficient, therefore we introduced the net joint moment obtained from the inverse dynamics to optimize the predicted joint moment. Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. Ultimately, this typical "FL training + local adaptation" PFL method can enhance model predictive accuracy by automatically generating a highly personalized model for each ICU center, guided by the FL sharing model. …”
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