Journal of the Nigerian Society of Physical Sciences最新文献_第5页

A tuberculosis model with three infected classes 有三个感染等级的结核病模型

Journal of the Nigerian Society of Physical Sciences Pub Date : 2024-02-13 DOI: 10.46481/jnsps.2024.1881

A. Sangotola, S. B. Adeyemo, O. A. Nuga, A. E. Adeniji, A. J. Adigun

引用次数: 0

Differential and fuzzy differential sandwich theorems involving quantum calculus operators 涉及量子微积分算子的微分和模糊微分夹层定理

Journal of the Nigerian Society of Physical Sciences Pub Date : 2024-01-19 DOI: 10.46481/jnsps.2024.1832

I. R. Silviya, K. Muthunagai

引用次数: 0

A DFT study of the optoelectronic properties of B and Be-doped Graphene 关于 B 和掺杂 B 的石墨烯光电特性的 DFT 研究

Journal of the Nigerian Society of Physical Sciences Pub Date : 2024-01-01 DOI: 10.46481/jnsps.2024.1730

L. O. Agbolade, A. K. Y. Dafhalla, D. M. I. Zayan, T. Adam, A. Chik, A. A. Adewale, S. C. B. Gopinath, U. Hashim

引用次数: 0

Approximate analytical solution of fractional-order generalized integro-differential equations via fractional derivative of shifted Vieta-Lucas polynomial 通过移位 Vieta-Lucas 多项式的分数导数近似解析解分数阶广义积分微分方程

Journal of the Nigerian Society of Physical Sciences Pub Date : 2024-01-01 DOI: 10.46481/jnsps.2024.1821

Kazeem Issa, Risikat A. Bello, Usman Jos Abubakar

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Carbon (IV) oxide adsorption efficiency of functionalized HKUST-1, IRMF-1, and UiO-66 metal organic frameworks 功能化 HKUST-1、IRMF-1 和 UiO-66 金属有机框架的氧化碳 (IV) 吸附效率

Journal of the Nigerian Society of Physical Sciences Pub Date : 2024-01-01 DOI: 10.46481/jnsps.2024.1673

Abdullahi Moyosore, Haslina Ahmad, Muhammad Alif, Muhammad Latif, Yousefzadeh Borzehandani, Mohd Basyaruddin AbdulRahman, Emilia Abdelmalek

引用次数: 0

Fractional-order modeling of visceral leishmaniasis disease transmission dynamics : strategies in eastern Sudan 内脏利什曼病疾病传播动态的分数阶建模：苏丹东部的策略

Journal of the Nigerian Society of Physical Sciences Pub Date : 2023-11-30 DOI: 10.46481/jnsps.2023.1693

Ghada A. Ahmed

引用次数: 0

Robust hybrid algorithms for regularization and variable selection in QSAR studies 用于 QSAR 研究中正则化和变量选择的稳健混合算法

Journal of the Nigerian Society of Physical Sciences Pub Date : 2023-11-28 DOI: 10.46481/jnsps.2023.1708

Christian N. Nwaeme, A. F. Lukman

{"title":"Robust hybrid algorithms for regularization and variable selection in QSAR studies","authors":"Christian N. Nwaeme, A. F. Lukman","doi":"10.46481/jnsps.2023.1708","DOIUrl":"https://doi.org/10.46481/jnsps.2023.1708","url":null,"abstract":"This study introduces a robust hybrid sparse learning approach for regularization and variable selection. This approach comprises two distinct steps. In the initial step, we segment the original dataset into separate training and test sets and standardize the training data using its mean and standard deviation. We then employ either the LASSO or sparse LTS algorithm to analyze the training set, facilitating the selection of variables with non-zero coefficients as essential features for the new dataset. Secondly, the new dataset is divided into training and test sets. The training set is further divided into k folds and evaluated using a combination of Random Forest, Ridge, Lasso, and Support Vector Regression machine learning algorithms. We introduce novel hybrid methods and juxtapose their performance against existing techniques. To validate the efficacy of our proposed methods, we conduct a comprehensive simulation study and apply them to a real-life QSAR analysis. The findings unequivocally demonstrate the superior performance of our proposed estimator, with particular distinction accorded to SLTS+LASSO. In summary, the twostep robust hybrid sparse learning approach offers an effective regularization and variable selection applicable to a wide spectrum of real-world problems.","PeriodicalId":342917,"journal":{"name":"Journal of the Nigerian Society of Physical Sciences","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139219554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A class of single-step hybrid block methods with equally spaced points for general third-order ordinary differential equations 一般三阶常微分方程的一类等间距点单步混合分块法

Journal of the Nigerian Society of Physical Sciences Pub Date : 2023-11-28 DOI: 10.46481/jnsps.2023.1484

M. Orakwelu, O. Otegbeye, Hermane Mambili-mamboundou

引用次数: 0

Typhoid fever dynamical model with cost-effective optimalcontrol 具有成本效益优化控制的伤寒动态模型

Journal of the Nigerian Society of Physical Sciences Pub Date : 2023-11-28 DOI: 10.46481/jnsps.2023.1579

Kazeem A. Tijani, C. E. Madubueze, R. I. Gweryina

{"title":"Typhoid fever dynamical model with cost-effective optimalcontrol","authors":"Kazeem A. Tijani, C. E. Madubueze, R. I. Gweryina","doi":"10.46481/jnsps.2023.1579","DOIUrl":"https://doi.org/10.46481/jnsps.2023.1579","url":null,"abstract":"Typhoid fever is a highly communicable and infectious disease that can be fatal and causes severe complications if unattended to timely. The infection, at times, can be more complex, challenging, and impossible to treat as antibiotics become less effective. Hence, the effect of limited clinical efficacy of the antibiotics with corresponding relapse response to treatment on infected humans is considered in this paper by formulating a deterministic model for direct and indirect transmission mode of Typhoid infection. The basic reproduction number is analytically derived and used to implement the global sensitivity analysis. Following the sensitivity analysis result, the optimal control analysis is carried out and simulated numerically with four controls: sanitation and hygiene practice and awareness campaign control, sterilisation and disinfection control, the potency of antibiotics control and screening control. Finally, the cost-effectiveness analysis for infected and susceptible humans with four cases that compared fifteen strategies is analysed. The results indicate that the sanitation and hygiene practice and awareness campaign is good to implement for single control implementation, while for double control implementation, Strategy 6, which is the combination of Strategy 1 and the potency of antibiotics administered to typhoid patients, is the best to consider. Combining Strategy 6 and screening control is the most cost-effective for triple controls. Furthermore, the overall computation of cost-effectiveness among all the most cost-effective with all the controls combined suggests that sanitation and hygiene practice and awareness campaign is the most cost-effective strategy to implement for eradicating typhoid infection in the population and for preventing susceptible populations from contracting the bacteria.","PeriodicalId":342917,"journal":{"name":"Journal of the Nigerian Society of Physical Sciences","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139223242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hyper-parameter tuning for support vector machine using an improved cat swarm optimization algorithm 基于改进cat群优化算法的支持向量机超参数整定

Journal of the Nigerian Society of Physical Sciences Pub Date : 2023-09-08 DOI: 10.46481/jnsps.2023.1007

Silifat Adaramaja Abdulraheem, Salisu Aliyu, Fatima Binta Abdullahi

{"title":"Hyper-parameter tuning for support vector machine using an improved cat swarm optimization algorithm","authors":"Silifat Adaramaja Abdulraheem, Salisu Aliyu, Fatima Binta Abdullahi","doi":"10.46481/jnsps.2023.1007","DOIUrl":"https://doi.org/10.46481/jnsps.2023.1007","url":null,"abstract":"Support vector machine (SVM) is a supervised machine learning algorithm for classification and regression problems. SVM performs better when combined with other classifiers or optimized with an optimization algorithm. The SVM parameters such as kernel and penalty have good performance on the classification accuracy. Recently, a lot of evolutionary optimization algorithms were used for optimizing the SVM. In this paper, an Improved Cat Swarm Optimization (ICSO) was proposed for optimizing the parameters of SVM with the aim of enhancing its performance. CSOs have the problem of a low convergence rate and are easily trapped in local optima. To address this problem, a new parameter was added to the velocity for the tracing mode and the Opposition-Based Learning (OBL) technique was used to modify the CSO algorithm (ICSO-SVM). A new parameter was introduced to guide the cats’ positions to the local and global best positions in the velocity tracing mode of the CSO algorithm. The proposed algorithm was verified using 15 datasets from the University of California Irvine (UCI) data repository and also six different performance metrics were used. The experimental results clearly indicate that the proposed method performs better than the other state-of-the-art methods.","PeriodicalId":342917,"journal":{"name":"Journal of the Nigerian Society of Physical Sciences","volume":"295 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116168123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0