Fuzzy logic algorithm for runoff-induced sediment transport from bare soil surfaces

Utilizing the rainfall intensity, and slope data, a fuzzy logic algorithm was developed to estimate sediment loads from bare soil surfaces. Considering slope and rainfall as input variables, the variables were fuzzified into fuzzy subsets. The fuzzy subsets of the variables were considered to have triangular membership functions. The relations among rainfall intensity, slope, and sediment transport were represented by a set of fuzzy rules. The fuzzy rules relating input variables to the output variable of sediment discharge were laid out in the IF-THEN format. The commonly used weighted average method was employed for the defuzzification procedure. The sediment load predicted by the fuzzy model was in satisfactory agreement with the measured sediment load data. Predicting the mean sediment loads from experimental runs, the performance of the fuzzy model was compared with that of the artificial neural networks (ANNs) and the physics-based models. The results of showed revealed that the fuzzy model performed better under very high rainfall intensities over different slopes and over very steep slopes under different rainfall intensities. This is closely related to the selection of the shape and frequency of the fuzzy membership functions in the fuzzy model

An Analysis of Vehicular Traffic Flow Using Langevin Equation

Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes

The influence of the surface topography of distributed sensor networks on perception

International Conference on Artificial Intelligence, ICAI 2012; Las Vegas, NV; United States; 16 July 2012 through 19 July 2012This work investigates the effects of surface topography of the distributed sensor networks on perception through the differences in sensor readings. Compound eyes are found in some insects and crustaceans. Lateral inhibition is a biological signal processing which can increase contrast, enhancing perception. It is known that eye convexity helps increase field of view (FOV). A series of experiments were carried out to understand the effect of surface topography on local contrast gradient. Two sets of sensor networks of 5 × 5 were constructed. In the first network the board holding the sensors was a flat circuit board, whereas the second one was given a radius of curvature of roughly 30 cm. All readings were recorded in a dark chamber. Sensor networks were illuminated by a light source whose coordinates could be adjusted. Results are tabulated. It is seen that eye convexity in compound eyes improves perception, as well as FOV

Local sparse coding control of CVPSTs

This paper discusses simulations of a control scheme based on locally sparse coded networks (CMACs) for a novel previously proposed continuously variable transmission (CVT), a hybrid continuously variable power split transmission (CVPST) (Osdemir and Schueller, 2002). Automotive transmissions match the speed and the torque of the power source to the speed and torque requirements of the load. Properly designed CVTs have shown potential to improve efficiency and performance. The main advantage of CMACs is fast computation because of their simple operational principles. Simulation results have shown that memory contents either reach a stable limit cycle or an attractor based on the selection of network parameters and the training method. Both online and offline training are possible

Power transmission entropy

Mechanical transmissions have been characterised traditionally by their transmission efficiencies. This is given by the ratio of the output to the input of the transmitted power. Unfortunately, the power transmission phenomenon is slightly more complex than that. As any designer would agree, each of these transmission localities is a source of uncertainty. Once formulated, this statement of uncertainty would reflect the designer's trust in the transmission. By virtue of the proposed approach, power transmission is no longer a deterministic entity but becomes a probabilistic one. This paper discusses the overlooked uncertainty inherent in every transmission

Measures of uncertainty in power split systems

This paper discusses the overlooked uncertainty inherent in every transmission. The uncertainty aspect has been often, for the sake of clarity, ignored. Instead, mechanical transmissions have been characterized traditionally by their transmission efficacies. It is known that transmission localities are sources of power loss, depending on many factors, hence sources of uncertainty. Thus each transmission of power should not only be designated by a constant of efficiency but also by an expression of uncertainty, reflecting the probability of transmission. Furthermore, Shannon's and Renyi's expressions of entropy have been used to quantify this so-called transmission uncertainty. The entropy of a transmitting unit is given in these two forms and then compared. Practical formulations for flow optimization are given

Classification of manipulators of the same origin by virtue of compactness and complexity

This work deals with a classification method that employs concepts such as complexity and compactness. The idea is to classify manipulators, or any other mechanism for that matter, of the same origin, based on the geometry of the joints, the tasks performed by the joints, the efficiency and the manufacturing cost to generate the specified efficiency. It is known that successive units on a single branch create individual uncertainties that affect the eventual quality of the performed operation [1]. An entropic expression quantifies this uncertainty in terms of the number of links and the unit effectiveness. The concepts of compactness and complexity have been formulated, and these concepts are explained through serial and parallel manipulators with varying parameters. Eventually, a cost function is created which is a function of complexity, uncertainty and the manufacturing cost. A worked example on M = 6 Stewart-Gough platform is given how this cost function could be taken advantage of when deciding an initial manipulator. A genetic algorithm is used for the optimization of the cost function, where the results are tabulated

A superstatistical model of vehicular traffic flow

In the analysis of vehicular traffic flow, a myriad of techniques have been implemented. In this study, superstatistics is used in modeling the traffic flow on a highway segment. Traffic variables such as vehicular speeds, volume, and headway were collected for three days. For the superstatistical approach, at least two distinct time scales must exist, so that a superposition of nonequilibrium systems assumption could hold. When the slow dynamics of the vehicle speeds exhibit a Gaussian distribution in between the fluctuations of the system at large, one speaks of a relaxation to a local equilibrium. These Gaussian distributions are found with corresponding standard deviations 1/β. This translates into a series of fluctuating beta values, hence the statistics of statistics, superstatistics. The traffic flow model has generated an inverse temperature parameter (beta) distribution as well as the speed distribution. This beta distribution has shown that the fluctuations in beta are distributed with respect to a chi-square distribution. It must be mentioned that two distinct Tsallis q values are specified: one is time-dependent and the other is independent. A ramification of these q values is that the highway segment and the traffic flow generate separate characteristics. This highway segment in question is not only nonadditive in nature, but a nonequilibrium driven system, with frequent relaxations to a Gaussian

An entropy-based analysis of lane changing behavior: An interactive approach

Objectives: As a novelty, this article proposes the nonadditive entropy framework for the description of driver behaviors during lane changing. The authors also state that this entropy framework governs the lane changing behavior in traffic flow in accordance with the long-range vehicular interactions and traffic safety. Methods: The nonadditive entropy framework is the new generalized theory of thermostatistical mechanics. Vehicular interactions during lane changing are considered within this framework. The interactive approach for the lane changing behavior of the drivers is presented in the traffic flow scenarios presented in the article. According to the traffic flow scenarios, 4 categories of traffic flow and driver behaviors are obtained. Through the scenarios, comparative analyses of nonadditive and additive entropy domains are also provided. Results: Two quadrants of the categories belong to the nonadditive entropy; the rest are involved in the additive entropy domain. Driving behaviors are extracted and the scenarios depict that nonadditivity matches safe driving well, whereas additivity corresponds to unsafe driving. Furthermore, the cooperative traffic system is considered in nonadditivity where the long-range interactions are present. However, the uncooperative traffic system falls into the additivity domain. The analyses also state that there would be possible traffic flow transitions among the quadrants. This article shows that lane changing behavior could be generalized as nonadditive, with additivity as a special case, based on the given traffic conditions. Conclusions: The nearest and close neighbor models are well within the conventional additive entropy framework. In this article, both the long-range vehicular interactions and safe driving behavior in traffic are handled in the nonadditive entropy domain. It is also inferred that the Tsallis entropy region would correspond to mandatory lane changing behavior, whereas additive and either the extensive or nonextensive entropy region would match discretionary lane changing behavior. This article states that driver behaviors would be in the nonadditive entropy domain to provide a safe traffic stream and hence with vehicle accident prevention in mind

Determining the complexity of multi-component conformal systems: A platoon-based approach

Many systems in nature and engineering are composed of subsystems. These subsystems may be formed in a linear, planar or spatial array. A typical example of these formations is a chain of vehicles known as platoon formation in traffic flow. Platoon formation of vehicles is a linear or planar formation of vehicles where a certain and a constant headway, and sideway if applicable, is provided in between every and each one of them. It is argued in this paper that a well-automated platoon formation of vehicles is an extreme case of conformity. During this transformation from a many degrees of freedom formation to a solid object, Tsallis q value is computed to be ranging from one extreme case of q=3 to the other where q=1, when classified in terms of inverse temperatures of clearance fluctuations. At one extreme of q=3, one observes unbounded fluctuations in clearance fluctuations so that inverse temperature distributions approach a Dirac delta at the origin. At the other extreme of q=1, fluctuations in clearance tend to zero asymptotically, where a solid structure of agents (vehicles) emerges. The transition from q=3 to q=1 is investigated through synthetic and experimental clearance fluctuations between the cars. The results show that during the transition from q=3 to q=1, the platoon loses its many degrees of freedom (dof) of motion until a solid single object emerges. Authors assert that the Tsallis q value of a platoon of vehicles is limited to 3>q<1