Search Results - (( parameter evaluation case algorithm ) OR ( leaf optimization methods algorithm ))
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Automated plant classification system using a hybrid of shape and color features of the leaf
Published 2016“…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
Published 2024“…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
Published 2013“…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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T-way testing : a test case generator based on melody search algorithm
Published 2015“…Next, TTT-MS will be executed through main algorithms to generate Parameters Interaction List, Parameter Values Interaction List, and finally generate final Test Cases based on Melody Search Algorithm. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
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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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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Hyperdize Jaya Algorithm for Harmony Search Algorithm's Parameters Selection
Published 2016“…This paper present a successful method to tune the parameters of the harmony search algorithm, which is a well-known meta-heuristic algorithm. …”
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A Preliminary Study on Camera Auto Calibration Problem Using Bat Algorithm
Published 2013“…This paper attempts to implement a stochastic optimization algorithm called Bat Algorithm in order to find optimal values of the intrinsic parameters. …”
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A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…By studying the echolocation behavior of the microbats, the bats will try to improve the fitness with each iteration. The Bat Algorithm's performance is evaluated using a case study from a database from Le2i Universite de Bourgoune. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…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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Using algorithmic taxonomy to evaluate lecture workload: a case study of services application prototype in the UPM KM Portal
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Identification of non-linear dynamic systems using fuzzy system with constrained membership functions
Published 2004“…It was found that, in most cases, the CFS performs better than the SFS with similar number of adjustable parameters. …”
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Using algorithmic taxonomy to evaluate lecture workload: A case study of services application prototype in the UPM KM portal
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Kalman filter based impedance parameter estimation for transmission line and distribution line
Published 2019“…Therefore, a detailed study on developing and evaluating the new algorithms for transmission line parameter estimation is considered in this thesis. …”
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Enhancing battery state of charge estimation through hybrid integration of barnacles mating optimizer with deep learning
“…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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An Improved Hybrid of Particle Swarm Optimization and the Gravitational Search Algorithm to Produce a Kinetic Parameter Estimation of Aspartate Biochemical Pathways
Published 2017“…However, measuring these parameters is typically difficult and even impossible in some cases. …”
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Parameter estimation of cocomo model using the jaya algorithm for software cost estimation
Published 2019“…The Constructive Cost Model (COCOMO) is a procedural software cost estimation model developed by Barry W. Boehm. In this case, the estimation of value of the COCOMO model parameters are determined for the cost and time estimation of the COCOMO model. …”
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Undergraduates Project Papers -
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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