Search Results - (( parameter realization _ algorithm ) OR ( leaf optimization method algorithm ))

Automated plant classification system using a hybrid of shape and color features of the leaf by Hamid, Laith Emad

“…Automated plant leaf classification is a computerized approach that employs computer vision and machine learning algorithms to identify a plant based on the features of its leaf. …”
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Leaf condition analysis using convolutional neural network and vision transformer by Yong, Wai Chun, Ng, Kok Why, Haw, Su Cheng, Naveen, Palanichamy, Ng, Seng Beng

“…Besides, existing leaf disease detection programs do not provide an optimized user’s experience. …”
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Plant leaf recognition algorithm using ant colony-based feature extraction technique by Ghasab, Mohammad Ali Jan

“…Then, based on the characteristics of each species, decision making is done by means of ant colony optimisation as a search algorithm to return the optimal subset of features regarding the related species. …”
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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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Realization of microcontroller-based polarization control system with genetic algorithm by Mamdoohi, Ghazaleh, Esmaeilian-Marnani, Aida, Abas, Ahmad Fauzi, Samsudin, Khairulmizam, Hidayat, Ariya, Ibrahim, Noor Hisham, Mahdi, Mohd Adzir

“…To reach optimum performance, the code is optimized by using the best genetic parameter to achieve the fastest execution time. This algorithm consumes low size of memory besides providing fast speed. …”
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Parameter-Less Simulated Kalman Filter by Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Nor Azlina, Ab. Aziz, Saifudin, Razali

“…Further studies on the effect of P(0), Q and R values suggest that the SKF algorithm can be realized as a parameter-less algorithm. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, M. N. M., Kahar

“…In this study, a new metaheuristic algorithm, viz., Grey Wolf Optimizer (GWO), is employed to optimize the parameters of interest. …”
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Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). This method was demonstrated for the optimization of machining parameters for turning operation using conventional lathe machines. …”
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Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning by Zuriani, Mustaffa, Mohd Herwan, Sulaiman

“…In response to the growing importance of SoC estimation, this study introduces a hybrid approach called the Barnacles Mating Optimizer with Deep Learning (BMO-DL) for SoC of Nissan Leaf batteries. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

“…The combination of lvABC and cmABC algorithm, which is later introduced as Enhanced Artificial Bee Colony–Least Squares Support Vector Machine (eABC-LSSVM), is realized in prediction of non renewable natural resources commodity price. …”
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Rice Predictive Analysis Mechanism Utilizing Grey Wolf Optimizer-Least Squares Support Vector Machines by Zuriani, Mustaffa, M. H., Sulaiman

“…In this regard, this study proposes a hybridization of LSSVM with a new Swarm Intelligence (SI) algorithm namely, Grey Wolf Optimizer (GWO). With such hybridization, the hyper-parameters of interest are automatically optimized by the GWO. …”
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Dengue outbreak prediction: hybrid meta-heuristic model by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin

“…Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. …”
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Improving PID controller of motor shaft angular position by using genetic algorithm by Muhamad, Arif Abidin

“…This study represents Genetic Algorithm optimization of PID parameters gain in model reference robust control system structure for desired position of incremental servomotor. …”
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Reduced Fuzzy Recursive Least-Squares Algorithm For Real Time Estimation by Cheah, Kah Wai

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Application of LSSVM by ABC in energy commodity price forecasting by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…The importance of the hyper parameters selection for a kernel-based algorithm, viz.Least Squares Support Vector Machines (LSSVM) has been a critical concern in literature.In order to meet the requirement, this work utilizes a variant of Artificial Bee Colony (known as mABC) for hyper parameters selection of LSSVM.The mABC contributes in the exploitation process of the artificial bees and is based on Levy mutation.Realized in crude oil price forecasting, the performance of mABC-LSSVM is guided based on Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSPE) and compared against the standard ABC-LSSVM and LSSVM optimized by Genetic Algorithm. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. …”
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Metaheuristic optimization of perovskite solar cell using hybrid L₃₂ Taguchi DoE-based genetic algorithm by Salehuddin, Fauziyah, Ahmad Jalaludin, Nabilah, Kaharudin, Khairil Ezwan, Arith, Faiz, Mohd Zain, Anis Suhaila, Md Junos@Yunus, Siti Aisah, R Apte, Prakash

“…This paper emphasizes the metaheuristic optimization approach in searching for the optimum input parameters of perovskite solar cell (PSC). The proposed approach is realized using Solar Cell Capacitance Simulator (SCAPS-1D) software incorporated with a hybrid L32 Taguchi DoE-based Genetic Algorithm. …”
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Optimisation of laser cutting parameters of oil palm wood / Harizam Mohd Zin by Harizam, Mohd Zin

“…In some cases, the prediction errors of Taguchi ANN model was found larger than 10% even using a Levenberg Marquardt training algorithm. To overcome the problem, a hybrid genetic algorithm-based Taguchi ANN (GA-Taguchi ANN) has been developed. …”
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