Tsp Solving by Hybridization of GA and AS

Joudaki, Majid; Imani, Mehdi; Mazhari, Niloofar

doi:10.7763/ijcee.2012.v4.637

Cited by 4 publications

(5 citation statements)

References 13 publications

(25 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results of our fit are shown in the second column of table I. They are in good accord with similar results found in [59].…”

Section: Planck Forecastsupporting

confidence: 90%

“…However, the value required to provide sufficient damping, dn s /d ln k ∼ −0.02, is much larger than expected from slow-roll inflationary models and would require a rethink of inflation and the generation of perturbations [57, 58] so we will not consider it further. Other examples of such parameters like an alternative model of dark energy, are considered in [59,60]. Here, we concentrate on a conventional, flat, ΛCDM model that we extend to include a parameter that has already been central to our discussion, namely, Y p .…”

Section: Planck Forecastmentioning

confidence: 99%

See 1 more Smart Citation

Increasing Neff with particles in thermal equilibrium with neutrinos

Boehm,

Dolan,

McCabe

2012

Preprint

View full text Add to dashboard Cite

Recent work on increasing the effective number of neutrino species (N eff ) in the early universe has focussed on introducing extra relativistic species ('dark radiation'). We draw attention to another possibility: a new particle of mass 10 MeV that remains in thermal equilibrium with neutrinos until it becomes non-relativistic increases the neutrino temperature relative to the photons. We demonstrate that this leads to a value of N eff that is greater than three and that N eff at CMB formation is larger than at BBN. We investigate the constraints on such particles from the primordial abundance of helium and deuterium created during BBN and from the CMB power spectrum measured by ACT and SPT and find that they are presently relatively unconstrained. We forecast the sensitivity of the Planck satellite to this scenario: in addition to dramatically improving constraints on the particle mass, in some regions of parameter space it can discriminate between the new particle being a real or complex scalar.

show abstract

“…The results of our fit are shown in the second column of table I. They are in good accord with similar results found in [59].…”

Section: Planck Forecastsupporting

confidence: 90%

Section: Planck Forecastmentioning

confidence: 99%

Increasing Neff with particles in thermal equilibrium with neutrinos

Boehm,

Dolan,

McCabe

2012

Preprint

View full text Add to dashboard Cite

show abstract

“…We, therefore, consider this work as a first step into the analysis of the role of cosmic strings as sources of extra radiation component in the universe, which demands further understanding of the underlaying cosmic string dynamics. Moreover, it would also be interesting to perform an analysis including extended cosmological parameters as in [74].…”

Section: Discussionmentioning

confidence: 99%

Correlations between cosmic strings and extra relativistic species

Lizarraga¹,

Sendra²,

Urrestilla³

2012

Phys. Rev. D

View full text Add to dashboard Cite

The recent observation that the Cosmic Microwave Background (CMB) may prefer a neutrino excess has triggered a number of works studying this possibility. The effect obtained by the non-interacting massless neutrino excess could be mimicked by some extra radiation component in the early universe, such as a cosmological gravitational wave background. Prompted by the fact that a possible candidate to source those gravitational waves would be cosmic strings, we perform a parameter fitting study with models which considers both cosmic strings and the effective number of neutrinos as free parameters, using CMB and non-CMB data. We find that there is a correlation between cosmic strings and the number of extra relativistic species, and that strings can account for all the extra radiation necessary. In fact, CMB data prefer strings at a 2sigma level, paying the price of a higher extra radiation component. CMB data also give a moderate preference for a model with ns=1. The inclusion of non-CMB data lowers both the preference for strings and for the extra relativistic species.Comment: 11 pages, 3 figures; Included new models in the analysis, matches the published versio

show abstract

“…Through the utilization of CRM, businesses can establish an infrastructure that fosters long-term and loyal customers. This concept is relevant across various industries, such as banking [1-4], insurance companies [5], and telecommunications [6][7][8][9][10][11][12][13][14], to name a few.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, it is imperative for businesses to develop practical tools to achieve this goal. In recent years, various ML methods have been proposed for constructing a churn model, including Decision Trees (DTs) [8][9][10][11][12][13][14][15][16], Artificial Neural Networks (ANNs) [8,9,[15][16][17], Random Forests (RFs) [18,19], Logistic Regression (LR) [9,12], Support Vector Machines (SVMs) [16], and a Rough Set Approach [20], among others.…”

Section: Introductionmentioning

confidence: 99%

Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis

Imani,

Arabnia

2023

Technologies

View full text Add to dashboard Cite

This paper explores the application of various machine learning techniques for predicting customer churn in the telecommunications sector. We utilized a publicly accessible dataset and implemented several models, including Artificial Neural Networks, Decision Trees, Support Vector Machines, Random Forests, Logistic Regression, and gradient boosting techniques (XGBoost, LightGBM, and CatBoost). To mitigate the challenges posed by imbalanced datasets, we adopted different data sampling strategies, namely SMOTE, SMOTE combined with Tomek Links, and SMOTE combined with Edited Nearest Neighbors. Moreover, hyperparameter tuning was employed to enhance model performance. Our evaluation employed standard metrics, such as Precision, Recall, F1-score, and the Receiver Operating Characteristic Area Under Curve (ROC AUC). In terms of the F1-score metric, CatBoost demonstrates superior performance compared to other machine learning models, achieving an outstanding 93% following the application of Optuna hyperparameter optimization. In the context of the ROC AUC metric, both XGBoost and CatBoost exhibit exceptional performance, recording remarkable scores of 91%. This achievement for XGBoost is attained after implementing a combination of SMOTE with Tomek Links, while CatBoost reaches this level of performance after the application of Optuna hyperparameter optimization.

show abstract

Tsp Solving by Hybridization of GA and AS

Cited by 4 publications

References 13 publications

Increasing Neff with particles in thermal equilibrium with neutrinos

Increasing Neff with particles in thermal equilibrium with neutrinos

Correlations between cosmic strings and extra relativistic species

Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis

Contact Info

Product

Resources

About