In this study, synthetic data with 100, 1000 and 2000 records have been produced to reflect the probabilities on the ALARM network. In this study, a medical diagnosis system called as DRCAD is presented. DRCAD system ...
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ISBN:
(纸本)9789814417730
In this study, synthetic data with 100, 1000 and 2000 records have been produced to reflect the probabilities on the ALARM network. In this study, a medical diagnosis system called as DRCAD is presented. DRCAD system is more innovative and interesting than the classical diagnosis support systems. In other words, DRCAD collects possible diagnosis of the patients from two sub modules. Each of these two sub modules gives the possible diagnosis from symptoms in a specific confidence degree. The proposal of two sub modules are combined linearly and diagnosis decisions are presented as a list. Each of the sub modules consist of Bayesian inference and rule-based inference models respectively. As a result, the methods in which the conclusions are combined in a linear manner are 5% more successful than the "Rule Based Method" when applied individually and 30% more successful than the cases where the "Bayesian Network Based Method" is utilized.
In collaborative systems (CS), procedures are performed by a team of professionals acting simultaneously, as in surgical rooms in medicine. Using Virtual Reality is possible to create virtual rooms that join people to...
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ISBN:
(纸本)9789814417730
In collaborative systems (CS), procedures are performed by a team of professionals acting simultaneously, as in surgical rooms in medicine. Using Virtual Reality is possible to create virtual rooms that join people to simulate those medical procedures. In such cases, collaborative features are used to coordinate the interactions of the multiple participants in the environment. To verify if the group performed the procedure correctly, assessment architectures has been proposed. However, network latency can affect that assessment. This paper presents a new architecture for adaptive assessment systems for training based on virtual reality for multiple users, which is able to solve that problem.
Recommender systems are effective approaches to implement personalised e-services. In recent years, they have gained widespread applications in e-commerce. Current recommender systems still need, however, further impr...
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ISBN:
(纸本)9789814417730
Recommender systems are effective approaches to implement personalised e-services. In recent years, they have gained widespread applications in e-commerce. Current recommender systems still need, however, further improvements with respect to the accuracy of prediction and to solve the scalability problem. To this end, an incremental collaborative filtering (InCF) algorithm based on the Mahalanobis distance is presented for recommender systems. Furthermore, the Mahalanobis radial basis function with ellipsoidal shape is employed to determine the decision boundaries of clusters. Experimental results show that the algorithm proposed can lead to improved prediction accuracy and that it turns out to be scalable in recommender applications.
In this paper, the uncertainty problem, including randomness and fuzziness as well as the medium mathematics background are introduced firstly. Then the two-phase uncertainty problem is described and two-phase degree ...
ISBN:
(纸本)9789814417730
In this paper, the uncertainty problem, including randomness and fuzziness as well as the medium mathematics background are introduced firstly. Then the two-phase uncertainty problem is described and two-phase degree (TPD), a measure method to the two-phase uncertainty, is introduced. Next, the SMS (Short Message Service) Spam in the mobile communication is studied as a two-phase uncertainty problem and a TPD of spam based algorithm is applied to make the spam filtering. The algorithm is combined the Naive Bayes based algorithm with the measure to the n-dimensional distance ratio mean function. The experiment result indicates that the TPD based algorithm is better than the classical Bayes based one and has practical value in current technical conditions.
In this study, rainfall-runoff modeling was carried out in Hajighoshan watershed using artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) with different inputs(current day rainfall;curre...
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ISBN:
(纸本)9789814417730
In this study, rainfall-runoff modeling was carried out in Hajighoshan watershed using artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) with different inputs(current day rainfall;current rainfall and pervious day rainfall;current rainfall, pervious day rainfall and two previous day) methods. Root mean squared error (RMSE), mean absolute error (MAE) and correlation coefficient (R) statistics are employed to evaluate the performance of the ANNs and ANFIS models for forecasting runoff. Comparison of the obtained results reveals that the ANFIS model outperforms the ANN models. Based on the results of test stage, ANFIS with RMSE=7.11 m3 s-1, MAE=2.18m3 s-1 and R=0.60 is superior to rainfall-runoff modeling than the ANN with RMSE=6.03m3 s-1, MAE=1.97 m3 s-1 and R=0.39.
Software cost estimation is one of the most important and complex tasks in software project management. As a result, several techniques for estimating development effort have been suggested. Fuzzy Analogy is one of th...
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ISBN:
(纸本)9789814417730
Software cost estimation is one of the most important and complex tasks in software project management. As a result, several techniques for estimating development effort have been suggested. Fuzzy Analogy is one of these techniques suggested to estimate project effort when it is described either by linguistic or numerical values. Based on reasoning by analogy and fuzzy logic, this technique uses fuzzy representation of software project attributes by using expert knowledge or clustering techniques. From this work, we evaluate the accuracy of this approach to estimate the software effort using the International Software Benchmarking Standards Group (ISBSG) repository.
In this paper, a single-period inventory problem with partially known demand information characterized by possibility distributions is analyzed. Decision models are proposed based on one-shot decision theory. Two choi...
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ISBN:
(纸本)9789814417730
In this paper, a single-period inventory problem with partially known demand information characterized by possibility distributions is analyzed. Decision models are proposed based on one-shot decision theory. Two choices are used for determining which state of nature (demand) should be considered for each order quantity. Based on the selected states of nature (focus point), the optimal order quantity is obtained. Different kinds of focus points (demands) lead to different results (optimal order quantities) which reflecting a decision maker's attitudes about possibility of demand and satisfaction of decision.
This paper presents a hybrid bees algorithm with a fuzzy logic controller (FLC-BA) to solve a pick and place robotic assembly line balancing problem. It aims to find the suitable tasks and components in order to defin...
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ISBN:
(纸本)9789814417730
This paper presents a hybrid bees algorithm with a fuzzy logic controller (FLC-BA) to solve a pick and place robotic assembly line balancing problem. It aims to find the suitable tasks and components in order to define the gripping strategies for each robot. Bees algorithms are designed using the natural foraging behavior of honey bees. A computational study is carried out and the results are compared with the results of an exact method deduced by Cplex. The experimental results show the advantages and the efficiency of the FLC-BA within a short computation time. This is the main advantage of our study as in our industrial application we are bounded by the time.
The heat transfer during boiling depends on a variety of factors (boiling stage, material parameters, geometrical parameters, state variables and flow conditions). All variations are based on empirical relationships g...
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ISBN:
(纸本)9789814417730
The heat transfer during boiling depends on a variety of factors (boiling stage, material parameters, geometrical parameters, state variables and flow conditions). All variations are based on empirical relationships gained from experimental data because there is still no comprehensive theory. With increasing wall superheat (Tw-Ts), the evaporation changes from convective boiling to nucleate boiling and then to film boiling. For each type of boiling, separate equations for the calculation of the heat transfer coefficient do exist. This paper presents possibilities to take account of the existing uncertainties in the dynamic simulation of boiling. For this reason a Takagi-Sugeno-fuzzy-model was developed which includes the fuzzy transitions between the boiling stages.
Our problem consists in scheduling both a production distributed on many sites and the transportation of items between those sites. The goal is to optimize the global solution. The production model adopted is a multi-...
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ISBN:
(纸本)9789814417730
Our problem consists in scheduling both a production distributed on many sites and the transportation of items between those sites. The goal is to optimize the global solution. The production model adopted is a multi-item, multi-level, Capacitated Lot-Sizing Problem. The transportation model is based on the Vehicle Routing Problem with discretized time. We present four heuristics based in matheuristics to solve it. Computational results are presented to evaluate the efficiency of the four heuristics.
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