A trend that is growing in visibility relates to the use of fuzzy logic in combination with neurocomputing and genetic algorithms. More generally, fuzzy logic, neurocomputing, and genetic algorithms may be viewe
The aim of this short note is twofold: recounting how our research group became interested in fuzzy logic, and briefly discussing a definition of fuzzy logic suggested by Bĕhounek and Cintula (see [1]doi:10.1007/978-3-642-35641-4-32Roberto Giuntini...
In the partnership of fuzzy logic, neuro- computing, and probabilistic reasoning, fuzzy logic is mainly concerned with imprecision and approximate reason- ing; neurocomputing with learning and curve-fitting; and probabilistic reason- ing with uncertainty and belief propa- gation. We can imagine this...
In large measure, the methodologies are complementary; and yet, there is an element of competition among them. In this setting, what makes sense is formation of a coalition. It is this perception that motivated the genesis of soft computing − a coalition of fuzzy logic, neurocomputing, ...
Unsupervised learning is a machine learning branch for interpreting unlabeled data. Discover how it works and why it is important with videos, tutorials, and examples.
Also, it is important to highlight that this paper focuses on how the decision-mak- ing process is conducted in unstable conditions; in other words, it focuses on how non-binary logic can further support organizations and their resilience in adapting to changing environments and adopting both ...
The next phase is the selection phase where methods are used to evaluate possible alternatives. This phase has two steps: evaluating and making decisions. Many methods can be used in the evaluating steps, such as fuzzy set,cloud computing,granular computingand some visualization tools like Gephi....
Chapter 13mainly addresses ways to adapt Critic and Action systems. It shows how to adaptanykind of parameterized differentiable Critic or Action system; it uses a notation which allows one to plug in a neural network, an adaptable fuzzy logic system, an econometric system, a soft gain-scheduli...
The emergence of new hardware architectures, and the continuous production of data open new challenges for data management. It is no longer pertinent to re
Applying the notation summarized in Table 1, a basic mixed-integer programming (MIP) model formulation for SALBP-1 is given in Fig. 1(a). Table 1. Notation for SALBP. n number of tasks (index j=1,…,n) V set of tasks V={1,…,n}; tasks are numbered according to a topological...