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214 results for “Problem solving”
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Research ArticleOpen accessIn the keywordsThe Best Candidates Method for Solving Optimization ProblemsHlayel Abdallah AhmadProblem statement: This study is about describing solution technique called Best Candidates Method (BCM) for solving optimization problems; the goal is to minimize the computation time to get the optimal solution. In this study I apply the BCM to the linear assignment problems (LAP) that is one of the optimization problems in the Operation Research (OR). Approach: The optimization problem … …Journal of Computer Science, Vol. 8, Issue 5 · 27 Feb 2012 · 8,341 accessesView PDFCite
Research ArticleOpen accessIn the keywordsInteractive Computing Framework for Engineering ApplicationsJovana Knezevic, Jerome Frisch, Ralf-Peter Mundani, Ernst RankProblem statement: Even though the computational steering state-of-the-art environments allow users to embed their simulation codes as a module for an interactive steering without the necessity for their own expertise in high-performance computing and visualisation, e.g., these environments are limited in their possible applications and mostly entail heavy code changes in order to integrate the existing code. Approach: In this … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,207 accessesView PDFCite
Research ArticleOpen accessIn the keywordsInciting Striving Speech (i.e., BS) and Imperfect Dialogical Exchanges is exactly what is needed in Higher Education TodayJames Carifio, Rocco PerlaHarry Frankfurt, the American moral philosopher, as well as his many advocates, has initiated a growing movement for eliminating BS from our culture and classrooms. BS is defined as people speaking beyond themselves on some topic that exceed their knowledge of the facts that are relevant to that topic. This article argues that BS and BS-ing (i.e., striving speech and … …Journal of Social Sciences, Vol. 4, Issue 1 · 31 Mar 2008 · 7,630 accessesView PDFCite
Research ArticleOpen accessIn the abstractReinforcement Learning in Financial Services: Modelling Payment Switching as a Multi-Armed Bandit ProblemIshaya Gambo, Christopher Agbonkhese, Segun Aina et al.The ever-evolving landscape of digital payments demands continuous innovation and self-improvement. This study addresses this imperative by simulating a model for payment routing, a crucial aspect of the digital payment ecosystem. To achieve this, industry professionals were interviewed to inform the approach, emphasizing data randomization for effective data collection. Using Python, a randomized dataset is created and three Reinforcement Learning … …Journal of Computer Science, Vol. 20, Issue 11 · 12 Oct 2024 · 4,710 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Background Knowledge and Random Sampling in Genetic Programming: A Case Study in Learning Boolean Parity FunctionsLappoon R. TangThe Boolean even-N-parity function returns T (i.e., true) if an even number of its Boolean arguments for N arguments are T and otherwise returns NIL (i.e., false). Learning Boolean even-N-parity functions has been recognized as a difficult problem for evolutionary computation (such as genetic programming) especially when N is large (e.g., 20+). A number of approaches have been proposed for … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 5,481 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Clustering using Two-Stage Eagle Strategy Based on Slime Mould AlgorithmRachid Oucheikh, Achraf Touil, Mouhsene FriDataclustering is considered an important component of data mining which aims tosplit a given dataset into disjoint groups having the same similarities. Thedeveloped techniques for clustering have some challenges to cluster entities incomplex search space and most of them aim to maximize the sum of inter-clusterdistances and minimize the sum of intra-cluster distances. This objectivefunction is nonlinear and hard to … …Journal of Computer Science, Vol. 18, Issue 11 · 7 Nov 2022 · 5,791 accessesView PDFCite
Research ArticleOpen accessIn the abstractPersian Curve Versus Monte Carlo MethodAbdolrasoul Ranjbaran, Mohammad Ranjbaran, Fatema RanjbaranThe Monte Carlo Simulation method is a powerfultool for solving problems including random variables. The basic idea toimplement a Monte Carlo simulation is to first generate samples of randominputs from their assumed distributionfunctions and then perform a deterministic calculation on the generated randominputs, based on mathematical modeling of the system, to obtain output results.An early version of Monte Carlo simulation … …International Journal of Structural Glass and Advanced Materials Research, Vol. 5, Issue 1 · 6 Jul 2021 · 8,300 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Quantitative Analysis of Preparedness and Performance: Predictive Indicators in First-Year Tertiary MathematicsGurudeo Anand TularamStudent preparedness at university entry plays a critical role in determining success in mathematics courses. This study investigates how three observable behaviours: (1) completion of weekly problem sets, (2) regular tutorial attendance, and (3) performance on a mid-semester test. We investigate how they relate to each other and their final examination results. Over five years, data were collected from 450 … …Journal of Social Sciences, Vol. 21, Issue 1 · 10 Oct 2025 · 2,724 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Learning Capability of an Agent in SOAR: Using 8-Queens ProblemNeha Rajan, Sunderrajan SrinivasanCognitive architecture deals with describing the intelligent behavior of an agent. The description of intelligent behavior states how well an agent can solve and represent variety of problems of the domain-independent task. The intelligence of an agent is considered in terms of its learning capabilities. In this study, we are exploring solving 8-Queens combinatorial problem using SOAR symbolic cognitive architecture. … …Journal of Computer Science, Vol. 16, Issue 5 · 25 May 2020 · 7,067 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCODIAG Select and Test (ST) Algorithm: An Approximate Clinical Reasoning Model for Diagnosing and Monitoring Breast CancerO.N. Oyelade, A.A. Obiniyi, S.B. JunaiduClinical reasoning involves coordinated thinking strategies targeted at gathering and analyzing relevant information to arrive at a high-quality clinical solution to patients' medical problems. The correctness and proper choice of clinical reasoning approach chosen by a clinician or machine affect the accuracy and acceptability of the diagnosis; moreover, another challenge that usually surfaces during clinical reasoning is the burden of … …Current Research in Bioinformatics, Vol. 9, Issue 1 · 22 Feb 2020 · 8,936 accessesView PDFCite