Valafar, Fararnarz. Ph.D., Purdue University, August 1993. PARALLEL PROBABILISTIC SELF-ORGANIZING HIERARCHICAL NEURAL NETWORKS. Major Professor: Okan K. Ersoy. A new neural network architecture called the Parallel Probabilistic Self-organizing Hierarchical Neural Network (PPSHNN) is introduced. The PPSHNN is designed to solve complex classification problems, by dividing the input vector space i...

0957-4174/$ see front matter 2013 Elsevier Ltd. A http://dx.doi.org/10.1016/j.eswa.2013.01.060 ⇑ Tel.: +385 1 4561191. E-mail address: [email protected] The main disadvantage of self-organizing polynomial neural networks (SOPNN) automatically structured and trained by the group method of data handling (GMDH) algorithm is a partial optimization of model weights as the GMDH algorithm optimizes on...

This paper proposes a novel clustering algorithm for the structure learning of fuzzy neural networks. Our clustering algorithm uses the reward and penalty mechanism for the adaptation of the fuzzy neural networks prototypes at every training sample. Compared with the classical clustering algorithms, the new algorithm can on-line partition the input data, pointwise update the clusters, and self-...

This paper investigates a self-organizing map algorithm which is simultaneously given multiple inputs, and introduces a criterion of ordering process as the twist measurement for reference vectors in multidimensional array. The self-organizing algorithm and the criterion are termed the parallel self-organizing algorithm and the index of twist, respectively. The algorithm updates reference vecto...

In this paper, a prototype system that focuses on affective design perspective for iterative product concept development is proposed and described. The prototype system, which emphasizes the solicitation of affective factors from both customers and designers, employs a sorting technique, i.e. picture sorts, for acquiring customer affect and a hierarchical structure for representing affective cr...

Identification of the short DNA sequence motifs that serve as binding targets for transcription factors is an important challenge in bioinformatics. Unsupervised techniques from the statistical learning theory literature have often been applied to motif discovery, but effective solutions for large genomic datasets have yet to be found. We present here three self-organizing neural networks that ...

Attention is drawn to the possibility that self-organizing biological neural networks could spontaneously acquire the capability to carry out sophisticated computations. In particular, it is shown that the effective action governing the organization of feature detectors in neural networks which incorporate Kohonen-like self-organization can spontaneously lead to structures that are topologicall...

Online public reviews have significant influenced customers who purchase products or seek services. Fake are posted online to promote demote targeted reputation of the organizations and businesses. Spam review detection has been focus many researchers in recent years. As services growing rapidly, importance issue is ever increasing needs be addressed properly. In this regard, there a variety ap...