Search Results - (( exploring model selection algorithm ) OR ( java code classification algorithm ))

Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…A formal algorithm that can be applied to any two related Java-based source codes examples is invented to generate the semantics of these source codes. …”
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Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

“…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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Metaheuristic algorithms for feature selection (2014–2024) by Faizan, Muhammad, Muhammad Arif, Mohamad

“…Feature selection is a process used during machine learning and data analysis, aimed at selecting the best features to increase model efficiency, decrease complexity, and increase readability. …”
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The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction by Adnan R.M., Kisi O., Mostafa R.R., Ahmed A.N., El-Shafie A.

An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…The “ensemble” model selected here to achieve better predictive performance, is used to predict future market price. …”
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Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

“…These techniques have demonstrated their superiority over traditional approaches in many CCRA studies. Machine learning model selection is an iterative process of exploring, evaluating, and improving algorithms. …”
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Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

“…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

“…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

“…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection by Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya

“…This research paper explores the performance of binary nature-inspired optimization algorithms as feature selection to enhance the identification of human activities using wearable technology. …”
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Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection by Iqbal, Muhammad

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Prior selection for Gumbel distribution parameters using multiple-try metropolis algorithm for monthly maxima PM10 data by Mohd Amin, Nor Azrita, Adam, Mohd Bakri, Ibrahim, Noor Akma

“…Several goodness of fit tests are compute for selecting the best model. The application is on the monthly maxima PM10 data for Johor state.…”
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Reactive memory model for ant colony optimization and its application to TSP by Sagban, Rafid, Ku-Mahamud, Ku Ruhana, Abu Bakar, Muhamad Shahbani

“…Reactive search is a framework for automating the exploration and exploitation in stochastic algorithms.Restarting the search with the aid of memorizing the search history is the soul of reaction.It is to increase the exploration only when needed.This paper proposes a reactive memory model to overcome the limitation of the random exploration after restart because of losing the previous history of search.The proposed model is utilized to record the previous search regions to be used as reference for ants after restart. …”
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Formulation of model predictive control algorithm for nonlinear processes by Mohd. Yusof, Khairiyah, Hassim, Mimi Haryani, Tan, Sook Li, Ab. Rashid, Siti Rafidah

“…To fulfil all these objectives, Model Predictive Control (MPC), an optimal model based control algorithm is definitely the best choice among all the advanced control algorithms available to date. …”
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Feature optimization with metaheuristics for Artificial Neural Network-based chiller power prediction by Nor Farizan, Zakaria, Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…The algorithm’s unique evolutionary mating mechanism with adaptive crossover rate (Cr = 0.85), enabled effective feature space exploration, resulting in a 38.3% reduction in RMSE and 6.0% improvement in R2 compared to models without feature selection. …”
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm by Azarberahman, Alireza, Tohidinia, Malihe, Aliakbarzadeh, Hossein

“…This study explores the application of intelligent algorithms, particularly the multi-objective of Strength Pareto Evolutionary Algorithm II (SPEA-II), alongside traditional methods to determine optimal portfolios. …”
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A novel single parent mating technique in genetic algorithm for discrete - time system identification by Abd Samad @ Mahmood, Md Fahmi, Zainuddin, Farah Ayiesya, Jamaluddin, Hishamuddin, Azad, Abul K. M.

“…As a popular search method, genetic algorithm (GA) is used for selecting a model structure. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…However, the developed algorithms only consider the selected features from a peak model based on the understanding of the EEG signals characteristics. …”
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Predicting the classification of heart failure patients using optimized machine learning algorithms by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md Maruf, Bhuiyan, Touhid

“…The optimized hyperparameters for the GBM model were identified using the AIW-PSO algorithm, which effectively balanced exploration and exploitation by adaptively adjusting inertia weights. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

“…The second component is a statistical machine learning mechanism named ACOustic to produce a robust exploration indicator. The third component is the ACO-based adaptive parameter selection algorithm to solve the parameterization problem which relies on quality, exploration and unified criteria in assigning rewards to promising parameters. …”
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