Industrial applications of soft computing: a review

Dote, Y.; Ovaska, S.J.

doi:10.1109/5.949483

Cited by 137 publications

(46 citation statements)

References 120 publications

(104 reference statements)

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“…Application domains such as battle management, logistics, signal analysis, targeting and tracking, counter-insurgency, as well as the development of intelligent auto pilots for UAV (swarms), among others, can, it is claimed, be better addressed by the methodologies purported in this paper than by any combination of conventional methodologies (e.g., case-based reasoning, expert systems, genetic algorithms, neural networks, support-vector machines, et al) [2].…”

Section: Need and Backgroundmentioning

confidence: 99%

“…This shows that the associative parsing mechanism is quite tractable for the typical query length of say ten words or so (i.e., even with subsequent normalization). Actually, since features may not embed other features, the complexity of associatively parsing symmetrically reduced queries, which is the general case, is actually much less, or (2 ) , where c is the number of such reductions and k is their average length.…”

Section: A Heuristic Evolutionary Feature Decompositionmentioning

confidence: 99%

“…A fundamental component of ISR technologies pertains to all levels of data fusion and extrapolation [2]. The greater need here is for methods that can parse natural language queries, map them to their semantic normalization, and retrieve information associatively tagged with the normalization in a seamless heterogeneous architecture.…”

Section: Introductionmentioning

confidence: 99%

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Geodesic search and retrieval of semi-structured databases

Rubin

Chen

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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Abstract-This paper addresses the learning of search-control knowledge expressed in semi-structured natural language. That knowledge is mined from semi-structured databases and applied to search the same. As is the case with most self-referential systems, this process necessarily addresses the issues of randomization, representation, machine learning, and evolutionary programming. Machine learning becomes pervasive at all levels of representation. That is, the randomization of knowledge necessarily includes that of its representation. Application to the search and retrieval of multimedia databases is suggested.

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Section: Need and Backgroundmentioning

confidence: 99%

Section: A Heuristic Evolutionary Feature Decompositionmentioning

confidence: 99%

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Geodesic search and retrieval of semi-structured databases

Rubin

Chen

2007

2007 IEEE International Conference on Systems, Man and Cybernetics

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“…The complication of flotation mechanism and interdependence of micro processes have been made evaluation and generation of quantitative and predictive model significantly difficult (Sherrell 2004;Do 2010;Amini 2012;Golshani et al 2013;Karimi et al 2014). Recent reviews on modeling methods reported that the number of soft computing based engineering models is increasing (Dote and Ovaska 2001). Soft computing is a collection of methodologies including fuzzy system, neural networks, and genetic algorithm which developed to eliminate imprecision and uncertainty of a nonlinear complex system (Kayak and Zadeh 1998).…”

Section: Introductionmentioning

confidence: 99%

Modeling of fine coal flotation separation based on particle characteristics and hydrodynamic conditions

Shahbazi

Chelgani

2016

Int J Coal Sci Technol

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Flotation is a complex multifaceted process that is widely used for the separation of finely ground minerals. The theory of froth flotation is complex and is not completely understood. This fact has been brought many monitoring challenges in a coal processing plant. To solve those challenges, it is important to understand the effect of different parameters on the fine particle separation, and control flotation performance for a particular system. This study is going to indicate the effect of various parameters (particle characteristics and hydrodynamic conditions) on coal flotation responses (flotation rate constant and recovery) by different modeling techniques. A comprehensive coal flotation database was prepared for the statistical and soft computing methods. Statistical factors were used for variable selections. Results were in a good agreement with recent theoretical flotation investigations. Computational models accurately can estimate flotation rate constant and coal recovery (correlation coefficient 0.85, and 0.99, respectively). According to the results, it can be concluded that the soft computing models can overcome the complexity of process and be used as an expert system to control, and optimize parameters of coal flotation process.

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“…Soft computing techniques 1 , are innovative approaches to construct a computationally intelligent system which can be used to tackle imprecision and uncertainty involved in a complex nonlinear system. Typically, these techniques consist of several computing methodologies, including neural networks 2 , fuzzy systems and genetic algorithm that have seen increasing interest in recent decade 3 . One popular and robust soft computing method is neuro-fuzzy technique which is the integration of fuzzy system and neural network.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study

Berneti¹

2013

IJCIS

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In this paper, a novel hybrid approach composed of adaptive neuro-fuzzy inference system (ANFIS) and imperialist competitive algorithm is proposed. The imperialist competitive algorithm (ICA) is used in this methodology to determine the most suitable initial membership functions of the ANFIS. The proposed model combines the global search ability of ICA with local search ability of gradient descent method. To illustrate the suitability and capability of the proposed model, this model is applied to predict oil flow rate of the wells utilizing data set of 31 wells in one of the northern Persian Gulf oil fields of Iran. The data set collected in a three month period for each well from Dec. 2002 to Nov. 2010. For the sake of performance evaluation, the results of the proposed model are compared with the conventional ANFIS model. The results show that the significant improvements are achievable using the proposed model in comparison with the results obtained by conventional ANFIS.

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Industrial applications of soft computing: a review

Abstract: Soft computing (SC) is an evolving collection of methodologies

Cited by 137 publications

References 120 publications

Geodesic search and retrieval of semi-structured databases

Geodesic search and retrieval of semi-structured databases

Modeling of fine coal flotation separation based on particle characteristics and hydrodynamic conditions

A Hybrid Approach Based on the Combination of Adaptive Neuro-Fuzzy Inference System and Imperialist Competitive Algorithm: Oil Flow Rate of the Wells Prediction Case Study

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