Prediction of rotor-spun yarn quality using hybrid artificial neural network-fuzzy expert system model

This study aims at developing a new approach to predict and determine the quality of rotor-spun yarn in terms of fibre characteristics as well as critical yarn properties. Hybrid modeling by combining two or more techniques has been demonstrated to give better performance than that of several single approaches over many research areas. Hence, in this study a hybrid model by combining two soft computing approaches, namely artificial neural network (ANN) and fuzzy expert system, has been developed. The ANN is used to predict three yarn characteristics, namely tenacity, breaking elongation and CVm. Then these three outputs are used to predict the new quality index by means of the fuzzy expert system. The accuracy of predicted model has been estimated using statistical performance criteria, such as correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE) and mean relative per cent error (MRPE). The results show the ability of model to predict the rotor-spun yarn quality and according to the analytical findings, the hybrid model gives accurate result.

Estimation des courbes Intensité-Durée-Aire-Fréquence (IDAF) de la région de Tunis dans un contexte multifractal

Due to its geographical position, Tunisia is subject to the influence of two climates, Mediterranean on the north and Saharan on the South, which are responsible for a significant spatio-temporal variability of rainfall. Particularly in recent years, sudden and intense rainfall that occurred in the area of Tunis, subject of our study, caused flooding with catastrophic consequences. This extreme variability of the rainfall field encouraged and motivated us to study the rainfall in this area. Multifractal analysis has shown its relevance in the characterization of geophysical process at high variability as the process of rainfall. Accordingly, in a first aspect, we investigated the occurrence of rainfall in monofractal context. We also studied the intensity of rainfall using the multifractal approach. The mono-fractal analysis has enabled us to emphasize firstly the particular behavior of the Mediterranean rainfall regime of Tunis area, characterized by a long dry season followed by a short rainy season. Then this analysis gave us an idea about the origin of intense rainfall which is likely due to isolated and convective cloud structures with low lifetime. Finally it showed a significant change in the fractal dimension of the support of rainfall during the last century. The spectral analysis and the study of the structure function have identified three regimes of scale invariance namely micro-scales, mesoscale and synoptic scale. Unlike the last two regimes, the process of rain during the first regime is non-conservative. In this case the rainfall intensity is not a pure multiplicative cascade. It results from a fractionally integrated multifractal cascade.However, it is recognized that the methods conventionally implemented to estimate the parameters of the universal multifractal model (MU) give rise to biased parameters in the case of rainfall. This is due to the intermittent nature of this process. The bias correction methods presented in the literature do not solve the problem in the case of time series recorded in Tunis given the importance of periods without rain, in other words, the intermittency of rainfall signal. For this reason, an empirical method of bias correction based mainly on the use of percentage of zero in a sequence of non-continuous rainfall has been proposed. For micro-scales, after bias correction, the parameters obtained are consistent both with those obtained on some events of continuous rain and those recently published on the properties of rainfall at fine scale.The establishment of curves (Intensity Duration Frequency) IDF, which links the return period, the intensity and duration of the rainfall, is a prerequisite for the design of hydraulic structures. Their development requires the availability of observations at sufficiently fine scales (5 minutes) and sufficiently long periods. Time series observed over sufficiently long periods (total daily rainfall and maximum annual rainfall intensities for fixed durations) allowed us to test the hypothesis of simple scale invariance of maximum annual rainfall intensities for different tipping bucket raingauge stations in Northern Tunisia. This assumption, combined with Gumbel modeling of maximum rainfall intensities allowed us to define a methodology for IDF curves development from the daily rainfall totals. A regionalization formula valuable for Northern Tunisia which involves the percentile 90% of the annual maximum daily rainfall was established and validated. This regionalization formula applied to daily data collected by the national hydrological service (DGRE) in 41  raingauges in the area of Tunis, combined with the assumption of simple scale invariance has enabled us to develop IDF curves of  raingauges in the area of Tunis for unobserved sites. A comparison between the slopes of IDF curves derived from probabilistic empirical Montana and American models established by adjusting statistical laws with the classical method and those derived from the highest-order of singularity and from the divergence moments order deduced of parameters of the universal multifractal model was conducted. The results are generally comparable. Thus, the parameters of the multifractal model lead to a consistent estimation of the slope of the IDF curves.Therefore, IDF curves were further used to create maps of rainfall quantiles for different durations and different return periods through the ArcView geographic information system software and using kriging as a spatial interpolation method. As a result, maps of quantiles gave an estimation of surfaces receiving rainfall quantile exceeding a fixed threshold, as a way for IDAF establishment. Moreover, in order to estimate curves IDAF (Intensity Duration Area Frequency) we used another approach proposed by De Michele et al. (2011) which refers to multifractal approach. It assumes that the maximum annual rainfall is distributed according to a log-normal distribution and the chronology of events of intense rainfall follows a Poisson distribution. It has been concluded that the Tunis Manoubia station verifies both assumptions for durations below two hours. Thereafter IDAF curves for durations less two hours, for return period less or equal to 100 years and for areas ranging to up to tens of km2 were estimated with reference to the empirical abatement coefficients of NERC (1975).Notre objectif est d’étudier les propriétés d’invariance d’échelles des précipitations observées à Tunis et leurs conséquences sur les courbes IDF et IDAF, préalable indispensable au dimensionnement des ouvrages hydrauliques. Des séries chronologiques de taux précipitant observés à Tunis ont été analysées. Plusieurs observations ont pu être faites : plusieurs régimes d’invariance d'échelle ; une évolution significative de la dimension fractale du support de la pluie à microéchelle au cours du siècle dernière; le caractère nonconservatif du régime microéchelle. Le modèle « multifractales universelles » caractérise les propriétés statistiques au moyen de trois paramètres. La prise en compte du caractère intermittent et non conservatif du processus de pluie à fine échelle conduit, à l’obtention de paramètres en accord avec les résultats récemment publiés sur les propriétés des précipitations à très fine échelle. L’établissement de courbes IDF, qui caractérisent la probabilité d’apparition des évènements intenses, nécessite de disposer d’observation à fine résolution (5mn) et sur de longues périodes (50 ans). Une relation de régionalisation appliquée aux données journalières recueillies par la DGRE dans 40 stations pluviométriques de la région du Grand Tunis, associée à l’hypothèse d’invariance d’échelle simple nous a permis d’élaborer les courbes IDF des stations pluviométriques de la région du Grand Tunis. Les courbes IDAF ont ensuite été élaborées à partir des cartes de quantiles déduites des courbes IDF d’une part, à partir de l’approche proposée par De Michele en 2011 d’autre part

Study of IDF curves established by the property of scale invariance in Tunis

This work focuses on the study of intensity-duration-frequency (IDF) curves of Tunis-Manoubia station located in Tunis (Tunisia). The assumption of simple scale invariance combined with the Gumbel distribution was used to develop the formulas of IDF curves. Indeed, firstly, the scale exponent was derived using all analyzed reference periods (5, 10, 15, 20, 30, 40, 50, 60, 90, 120, 180 minutes and 24 hours). It should be noted that the daily rainfall intensities are corrected using the coefficient of Weiss to obtain those of 24 hours. However, the study of probability weighted moments unveiled a scale break at 30 minutes. Hence, there are two intervals each one characterized by a simple scale invariance and a scale exponent namely [5 minutes - 30 minutes] and [30 minutes - 24 hours]. IDF curves obtained by simple scaling were compared with those experimental one determined by DGRE (Directorate General of Water Resources of Tunisia). It proved that the maximum intensities estimated by DGRE for different return times (2, 5, 10, 20, 58, 100 years) are overestimated for durations of references less than 30 minutes which is oversize hydraulic works, whose design is based on these curves such as dams and sewage works. Since the rainfall data at high resolution (minutes to hours) are not available because most stations are equipped with non-recording gauges. Only totals are available, hence the interest of this method is the estimation of maximum intensity for periods less than one day using only daily data

Investigation of the fractal dimension of rainfall occurrence in a semi-arid Mediterranean climate

International audienceThe scale invariance of rainfall series in the Tunis area, Tunisia (semi-arid Mediterranean climate) is studied in a mono-fractal framework by applying the box counting method to four series of observations, each about 2.5 years in length, based on a time resolution of 5 min. In addition, a single series of daily rainfall records for the period 1873-2009 was analysed. Three self-similar structures were identified: micro-scale (5 min to 2 d) with fractal dimension 0.44, meso-scale (2 d to one week) and synoptic-scale (one week to eight months) with fractal dimension 0.9. Interpretation of these findings suggests that only the micro-scale and transition to saturation are consistent, while the high fractal dimension relating to the synoptic scale might be affected by the tendency to saturation. A sensitivity analysis of the estimated fractal dimension was performed using daily rainfall data by varying the series length, as well as the intensity threshold for the detection of rain

Study of the occurrence of rain in the Tunis area in a mono-fractal framework

International audienceLess study concern the scale variability of the rainfall field in North Africa (Mediterranean climate), where the climate differ significantly from the Sahelian Africa (monsoon climate). This paper undertakes a study of the occurrence of rain in the region of Tunis in a mono-fractal framework. The box-counting method is applied to four series of observations of a continuous period of two and a half years, based on a minimum resolution of 5 min and belonging to the semi-arid bioclimatic stage. These series are characterized by strong intermittency. Using the sensor detection threshold, two self-similar structures were detected: micro-scale (5min- 2 days) with fractal dimension 0.44 and a synoptic-scale (one week - eight months) with fractal dimension of 0.9. This last value is probably overestimated by the presence of the saturation of the available space by rain (fractal dimension equal to one) for period longer than eight month. Due to the length of the dry period observed, the length of this saturation period differs from other studies performed in other area. Between the two self-similar structures a transitional regime corresponding to a meso-scale (2 days- one week) could be distinguished. The increase of the threshold would allow to 'filter' the frontal structure so as to keep only the convective structures, a sub micro-scale structure (5mn - 1h 20) has been detected with 0.3 mm/5mn intensity threshold. These results may reflect the influence of two distinctive types of convective showers and original front controlling these series

Estimation of intensity-duration-frequency relationships according to the property of scale invariance and regionalization analysis in a Mediterranean coastal area

International audienceUsually, networks of daily rainfall raingauges have a higher spatial cover than tippet bucket raingauges networks. Consequently, it would be of high interest to make use of daily rainfall information to asses IDF curves for unobserved locations. The present work proposes achieving this goal by using the assumption of simple scaling invariance. Indeed, series observed over sufficiently long periods for 10 tippet bucket raingauge, allowed us to test the hypothesis of simple scaling of annual maximum rainfall intensities in northern Tunisia. This assumption, combined with Gumbel model of maximum rainfall intensities allowed us to develop a methodology to estimate IDF curves from the daily rainfall totals. In fact, a regionalization formula which involves the percentile 90% of the annual maximum daily rainfall was developed and validated. This regionalization formula applied to daily data of 25 rainfall stations in the sub area of Tunis region, combined with the assumption of simple scaling has enabled us to develop Intensity Duration Area Frequency (IDAF) curves for Tunis area

Prediction of rotor-spun yarn quality using hybrid artificial neural network-fuzzy expert system model

31-38This study aims at developing a new approach to predict and determine the quality of rotor-spun yarn in terms of fibre characteristics as well as critical yarn properties. Hybrid modeling by combining two or more techniques has been demonstrated to give better performance than that of several single approaches over many research areas. Hence, in this study a hybrid model by combining two soft computing approaches, namely artificial neural network (ANN) and fuzzy expert system, has been developed. The ANN is used to predict three yarn characteristics, namely tenacity, breaking elongation and CVm. Then these three outputs are used to predict the new quality index by means of the fuzzy expert system. The accuracy of predicted model has been estimated using statistical performance criteria, such as correlation coefficient (R), root mean square error (RMSE), mean absolute error (MAE) and mean relative per cent error (MRPE). The results show the ability of model to predict the rotor-spun yarn quality and according to the analytical findings, the hybrid model gives accurate result

Regionalization of IDF curves using the property of scale invariance

Networks of daily rainfall raingauges are often much dense than tippet bucket raingages networks. Consequently, it would be of high interest to make use of daily rainfall information assessing IDF curves for unobserved locations. The present work proposes achieving this goal by using the assumption of simple scale invariance. The simple scaling property is identified using the fitting of regression of log transforms of rainfall statistical moments of order q versus log transforms of rainfall durations (scale). In case where the relation of slopes versus moment orders is linear, "simple scaling invariance" is assumed (Gupta et Waymire, 1990). Yu et al. (2004), Bara et al. (2009) as well as Ceresetti et al., (2010) adopted the assumptions of simple scaling to maximum annual rainfall for durations in the interval 30 mn to 24 h. Thus, using 24h-rainfall totals, they suggested estimating quantiles of rainfall intensities of short durations using quantiles of 24 h rainfall. In the present work, series constituted by the N most important maximum annual intensities observed during N years in 15 stations are studied. Observed intensities for various time resolutions extending from 5 minutes to 24 h are available. The period of observation is 1950 to 2001. Two simple scale invariance behaviors are identified namely a scale regime in the interval [5 minutes - 30 minutes] and another in the interval [30 minutes - 24 hours] for all stations. The study focuses on durations in the interval [30 minutes - 24 hours]. The resulting scale exponents vary from k=0.55 to k=0.89 for the resolutions [30 minutes - 24 hours] and vary from k=0.40 to k=0.65 for [5 minutes - 30 minutes] resolutions. Furthermore, for regionalization purposes, a power low regression is fitted and cross-validated between the estimated scale exponents and 90th percentile of sample maximum annual daily rainfall

Open-End Yarn Properties Prediction Using HVI Fibre Properties and Process Parameters

This article provides three models to predict rotor spun yarn characteristics which are breaking strength, breaking elongation and unevenness. These models used noncorrelated raw material characteristics and some processing parameters. For this purpose, five different cotton blends were processed into rotor spun yarns having different metric numbers (Nm10, Nm15, Nm18, Nm22, Nm30 and Nm37). Each count was spun at different twist levels. Response surface method was used to estimate yarn quality characteristics and to study variable effects on these characteristics. In this study, predicting models are given by the analysis of response surface after many iterations in which nonsignificant terms are excluded for more accuracy and precision. It was shown that yarn count, twist and sliver properties had considerable effects on the open-end rotor spun yarn properties. This study can help industrial application since it allows a quality management-prediction based on input variables such as fibre characteristics and process parameters