International Journal of Computing Science and Mathematics (6 papers in press)

Regular Issues

• The Application of Mathematical Analysis in Solving Nonlinear Phenomena in Fluid Mechanics  
  by You Li, Gui Li, Xuan Leng 
  Abstract: In order to assist mathematical analysis in solving nonlinear problems, reduce the computational cost and accelerate the solution process, the study explores the common mathematical methods for nonlinear solution; followed by the introduction of an optimized arithmetic algorithm for improved precision. Experimental results showed the hybrid algorithm designed in the study achieves a recall of 0.893, corresponding to a precision of 0.9, and a ROC region of 0.913, which is better than other algorithms in the same experimental environment. The algorithm demonstrated fast convergence in loss curve, high computational efficiency, taking only 9.07s. The average absolute value error converges to 0.07, and the root mean square error converges to 0.532. The method takes the optimal values of Generation Distance, Hyper volume, Spacing and Spread indexes in the process of solving nonlinear equations. This study effectively combines the mathematical analytical method and computer technology to provide a new idea and method for the mathematical analysis of nonlinear phenomena, which enriches the research content of nonlinear science.
  Keywords: Mathematical analysis method; Solitons; Abnormal wave; Nonlinear phenomena; Arithmetic optimization algorithm; Nonlinear equation.
  DOI: 10.1504/IJCSM.2025.10072716
   
  
• Machine Learning Approach for Classification of Phishing Attacks with Particle Swarm Optimisation Technique  
  by Prakash Pathak, Akhilesh Shrivas 
  Abstract: Phishing is an online scam where an attacker creates fake websites or emails to collect secret information from the internet or email users. The main contribution of research work is to develop a robust and computationally efficient hybrid model using machine learning based classification techniques with Particle Swarm Optimisation (PSO) to facilitate the classification of phishing attacks. The study constructs a machine learning-based ensemble model empowered by particle swarm optimisation for effective phishing attack classification. A novel ensemble model is developed, amalgamating Support Vector Machine(SVM), Logistic Regression(LR), and Decision Trees (DT) through a voting scheme ensemble technique. Additionally, PSO feature selection techniques are applied to phishing datasets to streamline feature sets. Comparative analysis with existing classifiers and ensemble models, employing reduced feature sets, demonstrates that our proposed model achieves a remarkable 99.08% accuracy with 27 features. Consequently, our recommended model offers expedited computational time for phishing attack classification.
  Keywords: phishing attacks; machine learning; classification; ensemble model; particle swarm optimization (PSO); 10-fold cross-validation.
  DOI: 10.1504/IJCSM.2025.10072717
   
  
• Optimisation of Algebraic Event Structure using Trace Equivalence based on Gr  
  by Weidong Tang, Weiwen Ge, Meiling Liu 
  Abstract: The process of data flow exchange in complex concurrent systems is often redundant and uncertain, leading to resource inefficiency and "state explosion". Equivalence relationships identify processes of the same behaviour, remove redundancy to simplify system verification and analysis, and effectively mitigate the "state explosion" problem. In Glabbeek's equivalence spectrum, trace equivalence (systems that produce the same sequence of actions are considered equivalent) and bi-simulation equivalence (requiring bidirectional behaviour correspondence between systems) are widely accepted. In this paper, we discuss the method of trace equivalence judgment on the polynomial algebraic event structure, propose the judgment of polynomial event equivalence, and use Grobner basis for calculation. Grobner basis, as an algebraic tool to determine the equality of polynomial systems, has the advantages of accuracy and efficiency, and provides a strict mathematical basis for the equivalence determination. Finally, a practical case is presented to show the optimisation effect of this method.
  Keywords: state explosion; trace equivalence; bisimulation equivalence; polynomial algebraic event structure; Gröbner basis.
  DOI: 10.1504/IJCSM.2025.10072982
   
  
• Linear Polynomial Algebra Migration System for Program Equivalence and Approximate Optimisation  
  by Weiwen Ge, Weidong Tang, Meiling Liu 
  Abstract: Program structure simplification constitutes a critical research domain in software engineering. With increasing system complexity, traditional simplification approaches remain predominantly confined to deterministic equivalence verification, lacking substantial investigation into approximate equivalence, error quantification, and control mechanisms. This paper develops a novel concept of common algebraic set bi-simulation equivalence by integrating Wu's characteristic series within a linear polynomial algebraic migration system framework. To address non-deterministic equivalence problems, this work introduces novel least squares solution metrics and singular value thresholding control mechanisms. These innovations establish an approximate bi-simulation equivalence theory that quantifies program behaviour differences while maintaining controllable error bounds. Consequently, approximately equivalent systems can replace the original complex systems, thereby simplifying program architecture. Experimental validation using a concurrent communication program demonstrates the efficacy of our proposed methodology in program optimisation.
  Keywords: Wu's characteristic series; linear polynomial algebra migration system; least squares solution; singular value thresholding; approximate bisimulation equivalence.
  DOI: 10.1504/IJCSM.2025.10073023
   
  
• News Recommendation Optimisation Path based on Improved GAT Algorithm  
  by Kunlong Yang, Minjing Wang 
  Abstract: To solve the problem of recommending massive news information mentioned above, a semantic representation model based on news text information fusion is proposed. The innovation lies in the use of capsule networks and Transformers for feature extraction and fusion, while proposing a perceptual model for graphic attention networks to enhance the capture of relevant information. In the accuracy recall analysis, the research model achieved an accuracy of 0.962 in sports news scenarios, which is superior to the other two models. In the comparison of recommendation accuracy, the model showed the best performance with recommendation accuracy of 0.915 and 0.961 on the Yahoo and MIND datasets, respectively. It can be seen that the research model meets the requirements of news and user development. The research content will provide important technical references for the effective dissemination of news and the improvement of recommendation techniques.
  Keywords: GAT; News recommendations; Capsule network; Transformer; Perception model.
  DOI: 10.1504/IJCSM.2025.10073091
   
  
• REC-YoloPose: a Lightweight Model for Enhancing Human Pose Estimation Performance in Multi-Scale and Complex Scenes  
  by Weize Chen, Chenyang Shi, Donglin Zhu, Changjun Zhou 
  Abstract: Human pose estimation is a computer vision research area, but it faces challenges in balancing model complexity and accuracy. To address this problem, this study proposes an improved model named REC-YoloPose, based on Yolov8sPose. Firstly, the contextual guidance (CG block) is employed to replace traditional convolution, and efficient local attention (ELA) is introduced into the backbone, enhancing the models feature extraction capability. Secondly, inspired by Repvit, the original Cross-Stage Partial fusion module (C2f) is improved, striking a balance between model parameters and recognition accuracy. Experimental results demonstrate that the proposed model achieves AP50 scores of 93.1% and 87.0% on Leeds sports pose (LSP) dataset and common objects in context (COCO) dataset respectively. Compared with other mainstream pose estimation algorithms, this model reduces computational parameters by 16.9% to 80.5% while maintaining high detection accuracy. Finally, REC-YoloPose is applied to human posture classification, showcasing its practical value in real-world tasks.
  Keywords: Human pose estimation;ELA;RepC2f;Context Guided Block;SMLP.
  DOI: 10.1504/IJCSM.2025.10073104