Search Results - risk optimization ((method algorithm) OR (means algorithm))

Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Alsarori, Ahmed Mohammed, Mohd Herwan, Sulaiman

“…The EMA-based model achieved superior results, with a Mean Absolute Error (MAE) of 0.018, Mean Squared Error (MSE) of 0.0006, Root Mean Squared Error (RMSE) of 0.024, and a coefficient of determination (R²) of 0.98 for risk prediction. …”
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Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin M.A.A., Ahmed A.N., Malek M.A., Mahmoud M.A., Sherif M., El-Shafie A.

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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm by Kusumawati, Rosita, Rosadi, Dedi, Abdurakhman, Abdurakhman

“…Risk-based portfolio optimization has become increasingly crucial due to the limitations and underperformance of traditional Mean-Variance (MV) portfolios. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review by Diandra Chika Fransisca, Sukono, Diah Chaerani, Nurfadhlina Abdul Halim

A new soft computing model for daily streamflow forecasting by Sammen S.S., Ehteram M., Abba S.I., Abdulkadir R.A., Ahmed A.N., El-Shafie A.

Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin, Mohammad Abdullah Abid, Ali, Najah Ahmed *, Marlinda, Abdul Malek, Moamin, A. Mahmoud, Sherif, Mohsen, El-Shafie, Ahmed

“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”
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Improving earth surface temperature forecasting through the optimization of deep learning hyper-parameters using barnacles mating optimizer by Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Muhammad 'Arif, Mohamad

“…To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management by Van Fu Shen, Fu Shen

“…The two stage stochastic risk model is then reformulated using Mean Absolute Deviation as the risk measure. …”
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Petroleum Refinery Planning Under Uncertainty: A Multiobjective Optimization Approach with Economic and Operational Risk Management by Van, Fu Shen

“…The two stage stochastic risk model is then reformulated using MeanAbsolute Deviation as the risk measure. …”
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Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

“…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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Multi-objective portfolio selection with skewness preference: An application to the stock and electricity markets / Karoon Suksonghong by Karoon, Suksonghong

“…The superiority of this method is its ability to generate a set of MVS efficient portfolios within a single run of algorithm. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm by Azarberahman, Alireza, Tohidinia, Malihe, Aliakbarzadeh, Hossein

“…The study highlights that the SPEA-II algorithm can serve as an effective and efficient method for stock portfolio selection and optimization, helping investors to identify portfolios with lower risk and higher return…”
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