Open Science Research Excellence
@article{(International Science Index):,
  title    = {Retrospective Reconstruction of Time Series Data for Integrated Waste Management},
  author    = {A. Buruzs and  M. F. Hatwágner and  A. Torma and  L. T. Kóczy},
  country   = {Hungary},
  institution={Széchenyi István University},
  abstract  = {The development, operation and maintenance of
Integrated Waste Management Systems (IWMS) affects essentially
the sustainable concern of every region. The features of such systems
have great influence on all of the components of sustainability. In
order to reach the optimal way of processes, a comprehensive
mapping of the variables affecting the future efficiency of the system
is needed such as analysis of the interconnections among the
components and modeling of their interactions. The planning of a
IWMS is based fundamentally on technical and economical
opportunities and the legal framework. Modeling the sustainability
and operation effectiveness of a certain IWMS is not in the scope of
the present research. The complexity of the systems and the large
number of the variables require the utilization of a complex approach
to model the outcomes and future risks. This complex method should
be able to evaluate the logical framework of the factors composing
the system and the interconnections between them. The authors of
this paper studied the usability of the Fuzzy Cognitive Map (FCM)
approach modeling the future operation of IWMS’s. The approach
requires two input data set. One is the connection matrix containing
all the factors affecting the system in focus with all the
interconnections. The other input data set is the time series, a
retrospective reconstruction of the weights and roles of the factors.
This paper introduces a novel method to develop time series by
content analysis.
    journal   = {International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering},  volume    = {8},
  number    = {12},
  year      = {2014},
  pages     = {3994 - 3997},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 96, 2014},