In the article we have discussed an approach to time series modelling based on Fuzzy Cognitive Maps (FCMs). We have introduced FCM design method that is based on replicated ordered time series data points. We named th...
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ISBN:
(纸本)9789897580741
In the article we have discussed an approach to time series modelling based on Fuzzy Cognitive Maps (FCMs). We have introduced FCM design method that is based on replicated ordered time series data points. We named this representation method history h, where h is number of consecutive data points we gather. Custom procedure for concepts/nodes extraction follows the same convention. The objective of the study reported in this paper was to investigate how increasing h influences modelling accuracy. We have shown on a selection of 12 time series that the higher the h, the smaller the error. Increasing h improves model's quality without increasing FCM's size. The method is stable - gains are comparable for FCMs of different sizes.
Standard assumption of pattern recognition problem is that processed elements belong to recognized classes. However, in practice, we are often faced with elements presented to recognizers, which do not belong to such ...
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ISBN:
(纸本)9789897580741
Standard assumption of pattern recognition problem is that processed elements belong to recognized classes. However, in practice, we are often faced with elements presented to recognizers, which do not belong to such classes. For instance, paper-to-computer recognition technologies (e.g. character or music recognition technologies, both printed and handwritten) must cope with garbage elements produced at segmentation level. In this paper we distinguish between elements of desired classes and other ones. We call them native and foreign elements, respectively. The assumption that we have only native elements results in incorrect inclusion of foreign ones into desired classes. Since foreign elements are usually not known at the stage of recognizer construction, standard classification methods fail to eliminate them. In this paper we study construction of recognizers based on support vector machines and aimed on coping with foreign elements. Several tests are performed on real-world data.
The objective of this work is to develop and implement a fuzzy controller and fuzzy fault detection for centralized chilled water system. Both controller and fault detector are implemented in supply air dampers of air...
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The objective of this work is to develop and implement a fuzzy controller and fuzzy fault detection for centralized chilled water system. Both controller and fault detector are implemented in supply air dampers of air handling unit (AHU). A few cases are tested in this paper to investigate the effectiveness of the developed systems. All simulation is carried out using MATLAB/SIMULINK. Results illustrate that the fuzzy controller is able to maintain rooms' temperature according to desired temperature whereas the fault detection can detect unusual behavior in supply air flow rate.
Learning and teaching computer programming have been acknowledged as being difficult and challenging. The metacognitive learning environment is needed for learning success in computer Programming problem solving. In d...
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Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user’s behavioural, physiological and psychological aspects. These aspects play critical ...
Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user’s behavioural, physiological and psychological aspects. These aspects play critical roles in user’s ability to assess the thermal environments. Previous studies have rarely addressed the effects of identified factors such as gender, age and locality on outdoor thermal comfort, particularly in hot, dry climate. This study investigated the thermal comfort of visitors at two city squares in Iran based on their demographics as well as the role of thermal environment. Assessing the thermal comfort required taking physical measurement and questionnaire survey. In this study, a non-linear model known as the neural network autoregressive with exogenous input (NN-ARX) was employed. Five indices of physiological equivalent temperature (PET), predicted mean vote (PMV), standard effective temperature (SET), thermal sensation votes (TSVs) and mean radiant temperature (T
mrt) were trained and tested using the NN-ARX. Then, the results were compared to the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS). The findings showed the superiority of the NN-ARX over the ANN and the ANFIS. For the NN-ARX model, the statistical indicators of the root mean square error (RMSE) and the mean absolute error (MAE) were 0.53 and 0.36 for the PET, 1.28 and 0.71 for the PMV, 2.59 and 1.99 for the SET, 0.29 and 0.08 for the TSV and finally 0.19 and 0.04 for the T
mrt.
Nowadays, mankind is facing several environmental challenges such as climate change, pollutions, etc. In order to create a more sustainable future, an adequate waste management system is necessary. One of the major so...
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The aim of this study was to investigate whether there are differences in the amplitude of the EMG signal among five different age groups of adolescent's muscle. Fifteen healthy adolescents participated in this st...
The aim of this study was to investigate whether there are differences in the amplitude of the EMG signal among five different age groups of adolescent's muscle. Fifteen healthy adolescents participated in this study and they were divided into five age groups (13, 14, 15, 16 and 17 years). Subjects were performed dynamic contraction during lifting a standard weight (3-kg dumbbell) and EMG signals were recorded from their Biceps Brachii (BB) muscle. Two common EMG analysis techniques namely root mean square (RMS) and mean absolute values (MAV) were used to find the differences. The statistical analysis was included: linear regression to examine the relationships between EMG amplitude and age, repeated measures ANOVA to assess differences among the variables, and finally Coefficient of Variation (CoV) for signal steadiness among the groups of subjects during contraction. The result from RMS and MAV analysis shows that the 17-years age groups exhibited higher activity (0.28 and 0.19 mV respectively) compare to other groups (13-Years: 0.26 and 0.17 mV, 14-years: 0.25 and 0.23 mV, 15-Years: 0.23 and 0.16 mV, 16-years: 0.23 and 0.16 mV respectively). Also, this study shows modest correlation between age and signal activities among all age group's muscle. The experiential results can play a pivotal role for developing EMG prosthetic hand controller, neuromuscular system, EMG based rehabilitation aid and movement biomechanics, which may help to separate age groups among the adolescents.
To evaluate performance of a large scale digital system, the system is modeled by stochastic timed petri nets (STPN) and performance index is estimated through iteration of a petri net simulation. When the performance...
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We introduce a Horn description logic called Horn-DL, which is strictly and essentially richer than Horn-RegI, Horn-SHIQ and Horn-SROIQ, while still has PTime data complexity. In comparison with Horn-SROIQ, Horn-DL ad...
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Recent development on distributed systems has shown that a variety of fairness constraints (some of which are only recently defined) play vital roles in designing self- stabilizing population protocols. Existing mod...
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Recent development on distributed systems has shown that a variety of fairness constraints (some of which are only recently defined) play vital roles in designing self- stabilizing population protocols. Existing model checkers are deficient in verifying the systems as only limited kinds of fair- ness are supported with limited verification efficiency. In this work, we support model checking of distributed systems in the toolkit PAT (process analysis toolkit), with a variety of fairness constraints (e.g., process-level weak/strong fairness, event-level weak/strong fairness, strong global fairness). It performs on-the-fly verification against linear temporal prop- erties. We show through empirical evaluation (on recent pop- ulation protocols as well as benchmark systems) that PAT has advantage in model checking with fairness. Previously un- known bugs have been revealed against systems which are designed to function only with strong global fairness.
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