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Optimal knowledge extraction technique based on hybridisation of improved artificial bee colony algorithm and cuckoo search algorithm

Sugumar R.

Int. J. Business Intelligence and Data Mining (Y):1-19 (2024)

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Enhancing Interpretability in Distributed Constraint Optimization Problems.M. Bhuvana Chandra C. Anand - 2025 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 8 (1):361-364.details Distributed Constraint Optimization Problems (DCOPs) provide a framework for solving multi-agent coordination tasks efficiently. However, their black-box nature often limits transparency and trust in decision-making processes. This paper explores methods to enhance interpretability in DCOPs, leveraging explainable AI (XAI) techniques. We introduce a novel approach incorporating heuristic explanations, constraint visualization, and modelagnostic methods to provide insights into DCOP solutions. Experimental results demonstrate that our method improves human understanding and debugging of DCOP solutions while maintaining solution quality. Download Export citation Bookmark
Predicting Insurance Charges Using Machine Learning (14th edition).Vivek Vishwakarma Smith Gholap - 2025 - International Journal of Innovative Research in Science Engineering and Technology 14 (2):1460-1463.details : In the realm of insurance, accurately predicting the charges or premiums that a policyholder will pay is a critical task. Traditional models may not fully capture the complexities involved due to the multifaceted nature of insurance data. This paper explores the use of machine learning (ML) techniques to predict insurance charges, providing a more data-driven and potentially more accurate method compared to conventional approaches. We will analyze various machine learning models, evaluate their performance, and discuss their potential for use (...) Download Export citation Bookmark
Wine Quality Prediction using Machine Learning.Abhishek Rathor Prajwal Wadghule - 2025 - International Journal of Multidisciplinary Research in Science, Engineering and Technology 8 (2):986-989.details Wine quality prediction is a significant task in the wine industry, as it helps producers and consumers determine the quality of a wine based on its chemical properties. Traditional methods of evaluating wine quality are subjective and time-consuming, relying on human tasters. However, with the advancement of machine learning (ML), it is now possible to predict wine quality in a more objective, scalable, and efficient manner. This paper explores various machine learning algorithms for predicting wine quality, evaluates their performance, and (...) Download Export citation Bookmark
Speech Emotion Recognition using Machine Learning and Librosa.Sivashree S. Pavithra J. - 2025 - International Journal of Advanced Research in Education and Technology 12 (1):224-228.details Emotion recognition from speech is an important aspect of human-computer interaction (HCI) systems, allowing machines to better understand human emotions and respond accordingly. This paper explores the use of machine learning techniques to recognize emotions in speech signals. We leverage the librosa library for feature extraction from audio files and train multiple machine learning models, including Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbors (k-NN), to classify speech emotions. The aim is to create an automated system capable of (...) Download Export citation Bookmark

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