Soft computing based model for trip production
A soft-computing approach to multi-item fuzzy eoq model incorporating discount his research interests focus on inventory and production management, fuzzy mathematics, interval mathematics, multi-objective optimisation and mathematical programming methods, etc. Purpose – cost estimation based on expert's judgment is not an ideal approach, since human decisions are usually determined according to general attributes of limited and unstructured experience the purpose of this paper is to develop a generic model of intelligence and cognitive science‐based method that can play an active role in process cost prediction within the shortest possible time. This article examines possibilities for the application of soft computing techniques for the prediction of travel demand the model, based on fuzzy logic and a genetic algorithm, successfully solves the trip distribution problem.
This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects it spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. The model was developed using two popular clustering techniques, namely gustafson–kessel (gk) and subtractive clustering (sc), and was extensively evaluated for performance based on various statistical indices. The aim and objectives of this research is to develop a soft computing based model for trip production, trip attraction & mode-wise traffic pattern in delhi urban area keeping in view the development polices of the delhi master plan 2021.
Soft computing is dedicated to system solutions based on soft computing techniques it provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems. Soft computing and software engineering (jscse) e-issn: 2251-7545 vol2,˛o7, 2012 to evaluate the accuracy of proposed prediction model based on acceptable criteria for final before releasing software to production defect prediction can also be observed from different. Prior to joining sas, holdaway was a senior geophysicist with shell oil, where he conducted seismic processing and interpretation and determined seismic attributes in 3d cubes for soft computing statistical data mining. Soft computing optimizer (sco) as a new software tool for design of robust intelligent control systems is described it is based on the hybrid methodology of soft computing and.
In this paper, a novel method based on hybrid soft computing techniques is used for permeability predictions the technique is known as adaptive network-based fuzzy inference systems or anfis, and is based on adaptive neural networks and fuzzy inference systems (fis. An aggregate production planning model for two phase production systems: solving with genetic algorithm and tabu search an analytic model-based approach for power system alarm processing employing temporal constraint network international journal of soft computing, vol 5, no 4. Optimized reservoir history matching simulation of canyon formation, sacroc unit, permian basin (soft computing) methods advanced resources international (ari) has performed two of these projects with in this third study performed by ari and also funded by the doe, a model-based. Approximation in effect, the role model for soft computing is the human mind the guiding principle of soft computing is: “exploit the tolerance for imprecision, using a group of c language integrated production system a multi agent system for clinical decision support is presented in  it uses memory based reasoning(mbr. The models and control strategies are combined to form two new model-based controllers that are more accurate and resilient than existing solutions resulting in increased power production.
Dr gokulachandran j and mohandas, k, “comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools”, journal of intelligent manufacturing, vol 26, pp 255–268, 2015. Soft computing models in big data governance big data expenditure minimization by means of machine learning and soft computing within smart cities and factories business models where leveraging machine learning and soft computing are used to enhance the quality of big data analytics and to unleash business potential. Fuzzy logic trip distribution gravity model soft computing fuzzy inference system home interview survey introduction the transportation planning process is a very important task in which the travel demand is estimated. Block diagram of model-based control of a grid-connected system solar radiation (g) and cell temperature (t c ) are measured, and are the inputs into both the model and the photovoltaic (pv) array. Shodhganga: a reservoir of indian theses @ inflibnet the [email protected] centre provides a platform for research students to deposit their phd theses and make it available to the entire scholarly community in open access.
Soft computing based model for trip production
131 chapter 13 trip generation ba ckg round in this chapter, the theory and mechanics of the trip gener ation stage will be explained trip generation is a model of the number of trips that originate and end in each zone for a given jurisdiction.  proposes a soft computing based approach towards intrusion detection using a fuzzy rule based system  suggests an approach based on machine learning techniques for intrusion detection. In the present paper one of the new generation soft computing technique that is known as gene expression programming (gep) is used to develop a meta-model from extensive simulation experiments for the multiple objective design of a production line.
Soft computing technique based economic load dispatch using biogeography-based optimization algorithm narottam dutt upadhyay1, rameshwar singh2 achieve the benefits of minimum production cost, better operating conditions and maximum reliability is the basic. International journal on soft computing, artificial intelligence and applications (ijscai), vol1, no3, december 2012 1 a novel multiplicative model of multi criteria analysis for robot selection bipradas bairagi 1, balaram dey 2, bijan sarkar 3 and subir sanyal 4 1department of production engineering, haldia institute of technology, haldia, india. Applied soft computing is an international journal promoting an integrated view of soft computing to solve real life problems soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost.
Some recent examples of soft computing techniques are fuzzy connectedness approaches to image segmentation, fuzzy clustering methods for products like leaf spot disease of cucumber images, optimization based products packing, deep/shallow neural network based inspection systems for agricultural products, etc. Aysenur bilgin , hani hagras , areej malibari , mohammed j alhaddad , daniyal alghazzawi, towards a linear general type-2 fuzzy logic based approach for computing with words, soft computing - a fusion of foundations, methodologies and applications, v17 n12, p2203-2222, december 2013. The production model is based on the idea that humans solve problems by applying their knowledge (expressed as production rules) to a given problem represented by problem-specific information the production rules are stored in the long-termmemory and the problem-specific information or facts in the short-term memory. Presented here is an application of soft-computing based on intelligent system this method will accept available data on each well, which includes basic well information and post-fracture production model coupled with cash flow model were used in their work the optimization was a of mathematical model using evolutionary computing.