Forthcoming articles

 


International Journal of Computational Complexity and Intelligent Algorithms

 

These articles have been peer-reviewed and accepted for publication in IJCCIA, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

 

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International Journal of Computational Complexity and Intelligent Algorithms (2 papers in press)

 

Regular Issues

 

  • Complexity Verification through Design and Analysis of Computer Experiments   Order a copy of this article
    by Niraj Singh, Soubhik Chakraborty, Dheeresh Mallick 
    Abstract: This research article is a systematic study towards exploring the parameterized behavior of smart sort, a comparison based sorting algorithm. Our observation for quick sort led us to conjecture that for sufficiently large samples of fixed size, the runtime complexity is: yavg(n, td) = Oemp(td). Performance of heap sort is better for discrete inputs with low k values (or equivalently high td values) and the runtime reaches to maximum beyond a threshold k. These two observations are opposite in their behavior. The smart sort, which is a designed of key functions of these two standard algorithms is expected to behave optimally with respect to all input parameters. The robustness of average case Oemp(nlog2n) complexity for smart sort is conjectured as result of study for various regression models and factorial design experiments.
    Keywords: Average case complexity; statistical bound; Empirical-O; quick sort; smart sort; parameterized complexity; factorial design; statistical significance.

  • GIS based Design and Analysis of Preventive Health Management System for Vehicles using ANFIS   Order a copy of this article
    by Sushma Kamlu 
    Abstract: The health of a vehicle gets affected by different parameters having uncertainties such as past running hours, vehicle operating condition, the consumption rate of fuel, etc., which in turn influence the health of a transportation system as a whole. In this work, a geographical information system (GIS) based Adaptive-Network-Based Fuzzy Inference System (ANFIS) has been utilized for the advanced prognostic and health management strategy of the vehicle to assess the condition of the vehicle from a precautionary preservation perspective, so as to enhance the ability of credentials of proactive malfunction circumstances. The case study corroborates the effectiveness of the proposed ANFIS technique. It provides the proposal of safeguarding the operation for pragmatic applications with consideration of all uncertainties, the domino effect on the health of the transportation system.
    Keywords: Vehicle health management system (VHMS); Geographical information system (GIS); Adaptive-Network-Based Fuzzy Inference System (ANFIS).