950 resultados para Aristotelian logic


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A new multi-output interval type-2 fuzzy logic system (MOIT2FLS) is introduced for protein secondary structure prediction in this paper. Three outputs of the MOIT2FLS correspond to three structure classes including helix, strand (sheet) and coil. Quantitative properties of amino acids are employed to characterize twenty amino acids rather than the widely used computationally expensive binary encoding scheme. Three clustering tasks are performed using the adaptive vector quantization method to construct an equal number of initial rules for each type of secondary structure. Genetic algorithm is applied to optimally adjust parameters of the MOIT2FLS. The genetic fitness function is designed based on the Q3 measure. Experimental results demonstrate the dominance of the proposed approach against the traditional methods that are Chou-Fasman method, Garnier-Osguthorpe-Robson method, and artificial neural network models.

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In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.

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In this study, simulation and hardware implementation of Fuzzy Logic (FL) Maximum Power Point Tracking (MPPT) used in photovoltaic system with a direct control method are presented. In this control system, no proportional or integral control loop exists and an adaptive FL controller generates the control signals. The designed and integrated system is a contribution of different aspects which includes simulation, design and programming and experimental setup. The resultant system is capable and satisfactory in terms of fastness and dynamic performance. The results also indicate that the control system works without steady-state error and has the ability of tracking MPPs rapid and accurate which is useful for the sudden changes in the atmospheric condition. MATLAB/Simulink software is utilized for simulation and also programming the TMS320F2812 Digital Signal Processor (DSP). The whole system designed and implemented to hardware was tested successfully on a laboratory PV array. The obtained experimental results show the functionality and feasibility of the proposed controller.

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In this paper, we presented an optimized fuzzy logic controller using particle swarm optimization for DC motor speed control. The controller model is simulated using MATLAB software and also experimentally tested on a laboratory DC motor. A comparison of the performance of different controllers such as PID controller, fuzzy logic controller and optimized fuzzy logic controller is presented as well. With reference to the results of digital simulations and experiment, the designed FLC-PSO speed controller obtains much better dynamic behavior compared to PID and the normal FLC designed. Moreover, it can acquire superior performance of the DC motor, and also perfect speed tracking with no overshoot. The optimized membership functions (MFs) are obviously proved to be able to provide a better performance and higher robustness in comparison with a regular fuzzy model, when the MFs were heuristically defined. Besides, experimental results verify the ability of proposed FLC under sudden change of the load torque which leads to speed variances.

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While comparative law has become a key discipline, its instrumentalist use has turned out to be a powerful weapon: it is the ‘pen’ by which the identity of and differences in law’s geopolitics are continually written and rewritten. Given its attractive functionalist essence, comparative law is gaining increasing international credit as a way of developing newer theories of sovereignty and governance in a framework in which law is conceived of less as a set of rules and more as a symbolic vestimentum of global soft power. The present contribution critically investigates the relationship between distortive views of comparative law’s geopolitics and the intimate essence of the doctrine aimed at creating the ‘aspatial’, unbounded, illimitable (and hence intangible) liberal global order whose governance appears to transcend the idea and form(s) of law through which the ‘politicization’ and ‘juridification’ of modernity have been achieved in the last century. In doing so, it also addresses why such an alliance has made it easier to ‘discover’ and ‘sell’ the smooth and rectilinear land of the figuratively unspoken and unwritten as the terra incognita that lies over what is created by the constructivist political intervention(s) of the modern nation-state

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This paper presents a novel design of interval type-2 fuzzy logic systems (IT2FLS) by utilizing the theory of extreme learning machine (ELM) for electricity load demand forecasting. ELM has become a popular learning algorithm for single hidden layer feed-forward neural networks (SLFN). From the functional equivalence between the SLFN and fuzzy inference system, a hybrid of fuzzy-ELM has gained attention of the researchers. This paper extends the concept of fuzzy-ELM to an IT2FLS based on ELM (IT2FELM). In the proposed design the antecedent membership function parameters of the IT2FLS are generated randomly, whereas the consequent part parameters are determined analytically by the Moore-Penrose pseudo inverse. The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. Effectiveness of the proposed design of IT2FLS is demonstrated with the application of forecasting nonlinear and chaotic data sets. Nonlinear data of electricity load from the Australian National Electricity Market for the Victoria region and from the Ontario Electricity Market are considered here. The proposed model is also applied to forecast Mackey-glass chaotic time series data. Comparative analysis of the proposed model is conducted with some traditional models such as neural networks (NN) and adaptive neuro fuzzy inference system (ANFIS). In order to verify the structure of the proposed design of IT2FLS an alternate design of IT2FLS based on Kalman filter (KF) is also utilized for the comparison purposes.

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A new paradigm is modeling the World: evolutionary innovations in all fronts, new information technologies, huge mobility of capital, use of risky financial tools, globalization of production, new emerging powers and the impact of consumer concerns on governmental policies. These phenomena are shaping the World and forcing the advent of a new World Order in the Multilateral Monetary, Financial, and Trading System. The effects of this new paradigm are also transforming global governance. The political and economic orders established after the World War and centered on the multilateral model of UN, IMF, World Bank, and the GATT, leaded by the developed countries, are facing significant challenges. The rise of China and emerging countries shifted the old model to a polycentric World, where the governance of these organizations are threatened by emerging countries demanding a bigger participation in the role and decision boards of these international bodies. As a consequence, multilateralism is being confronted by polycentrism. Negotiations for a more representative voting process and the pressure for new rules to cope with the new demands are paralyzing important decisions. This scenario is affecting seriously not only the Monetary and Financial Systems but also the Multilateral Trading System. International trade is facing some significant challenges: a serious deadlock to conclude the last round of the multilateral negotiation at the WTO, the fragmentation of trade rules by the multiplication of preferential and mega agreements, the arrival of a new model of global production and trade leaded by global value chains that is threatening the old trade order, and the imposition of new sets of regulations by private bodies commanded by transnationals to support global value chains and non-governmental organizations to reflect the concerns of consumers in the North based on their precautionary attitude about sustainability of products made in the World. The lack of any multilateral order in this new regulation is creating a big cacophony of rules and developing a new regulatory war of the Global North against the Global South. The objective of this paper is to explore how these challenges are affecting the Tradinge System and how it can evolve to manage these new trends.

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Investors were wrong to believe in change for the better; Brazil is stuck for at least two years

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A lógica fuzzy admite infinitos valores lógicos intermediários entre o falso e o verdadeiro. Com esse princípio, foi elaborado neste trabalho um sistema baseado em regras fuzzy, que indicam o índice de massa corporal de animais ruminantes com objetivo de obter o melhor momento para o abate. O sistema fuzzy desenvolvido teve como entradas as variáveis massa e altura, e a saída um novo índice de massa corporal, denominado Índice de Massa Corporal Fuzzy (IMC Fuzzy), que poderá servir como um sistema de detecção do momento de abate de bovinos, comparando-os entre si através das variáveis linguísticas )Muito BaixaM, ,BaixaB, ,MédiaM, ,AltaA e Muito AltaM. Para a demonstração e aplicação da utilização deste sistema fuzzy, foi feita uma análise de 147 vacas da raça Nelore, determinando os valores do IMC Fuzzy para cada animal e indicando a situação de massa corpórea de todo o rebanho. A validação realizada do sistema foi baseado em uma análise estatística, utilizando o coeficiente de correlação de Pearson 0,923, representando alta correlação positiva e indicando que o método proposto está adequado. Desta forma, o presente método possibilita a avaliação do rebanho, comparando cada animal do rebanho com seus pares do grupo, fornecendo desta forma um método quantitativo de tomada de decisão para o pecuarista. Também é possível concluir que o presente trabalho estabeleceu um método computacional baseado na lógica fuzzy capaz de imitar parte do raciocínio humano e interpretar o índice de massa corporal de qualquer tipo de espécie bovina e em qualquer região do País.

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The aim of this study was to develop a laboratory method for time response evaluation on electronically controlled spray equipment using Programmable Logic Controllers (PLCs). For that purpose, a PLC controlled digital drive inverter was set up to drive an asynchronous electric motor linked to a centrifugal pump on a experimental sprayer equipped with electronic flow control. The PLC was operated via RS232 serial communication from a PC computer. A user program was written to control de motor by adjusting the following system variables, all related to the motor speed: time stopped; ramp up and ramp down times, time running at a given constant speed and ramp down time to stop the motor. This set up was used in conjunction with a data acquisition system to perform laboratory tests with an electronically controlled sprayer. Time response for pressure stabilization was measured while changing the pump speed by +/-20%. The results showed that for a 0.2 s ramp time increasing the motor speed, as an example, an AgLogix Flow Control system (Midwest Technologies Inc.) took 22 s in average to readjust the pressure. When decreasing the motor speed, this time response was down to 8 s. General results also showed that this kind of methodology could make easier the definition of standards for tests on electronically controlled application equipment.

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This paper describes a novel approach for mapping lightning processes using fuzzy logic. The estimation process is carried out using a fuzzy system based on Sugeno's architecture. Simulation results confirm that proposed approach can be efficiently used in these types of problem.

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From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

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O método de combinação de Nelson-Oppen permite que vários procedimentos de decisão, cada um projetado para uma teoria específica, possam ser combinados para inferir sobre teorias mais abrangentes, através do princípio de propagação de igualdades. Provadores de teorema baseados neste modelo são beneficiados por sua característica modular e podem evoluir mais facilmente, incrementalmente. Difference logic é uma subteoria da aritmética linear. Ela é formada por constraints do tipo x − y ≤ c, onde x e y são variáveis e c é uma constante. Difference logic é muito comum em vários problemas, como circuitos digitais, agendamento, sistemas temporais, etc. e se apresenta predominante em vários outros casos. Difference logic ainda se caracteriza por ser modelada usando teoria dos grafos. Isto permite que vários algoritmos eficientes e conhecidos da teoria de grafos possam ser utilizados. Um procedimento de decisão para difference logic é capaz de induzir sobre milhares de constraints. Um procedimento de decisão para a teoria de difference logic tem como objetivo principal informar se um conjunto de constraints de difference logic é satisfatível (as variáveis podem assumir valores que tornam o conjunto consistente) ou não. Além disso, para funcionar em um modelo de combinação baseado em Nelson-Oppen, o procedimento de decisão precisa ter outras funcionalidades, como geração de igualdade de variáveis, prova de inconsistência, premissas, etc. Este trabalho apresenta um procedimento de decisão para a teoria de difference logic dentro de uma arquitetura baseada no método de combinação de Nelson-Oppen. O trabalho foi realizado integrando-se ao provador haRVey, de onde foi possível observar o seu funcionamento. Detalhes de implementação e testes experimentais são relatados