Fuzzy-logic Method for Global Quality Optimization Problem of the Programmed Action Investment

In order to analyze the planning of a transport linear infrastructure(railway or ordinary road),in order to optimize a relationship work-environment after-work,the study team(engineers,architects,economists,etc),realize a careful prearranged analysis about the characteristic of the site and the large area which are involved by the work project and,once one found all possible alternative solutions,he should compare them through the use of suitable technical,economical and environmental parameters,choosing that one which maximize the global utility of the public investment.In this paper we study a fuzzy-logic method in order to help the decision maker in the analysis of the programmed action public investment.

A Fuzzy-Logic Based Path Loss Model at 3.4 GHz for LTE Networks

Empirical and deterministic models have not proven to be effective in path loss predictions because of the problems of computational complexities, low accuracies, and inability to generalize. To solve these problems relating to path loss predictions, this article presents an optimal path loss propagation model developed at 3.4 GHz with the use of fuzzy logic. We introduced Fuzzy logic to accurately represent all forms of uncertainties in the data spectrum as the signal propagates from the transceiver to the receiver, thereby producing accurate results. Experimental data were collected across Cyprus at 3.4 GHz and compared with three existing path loss models. The fuzzy-logic path loss prediction model was then developed and compared with the experimental data and with each of the theoretical empirical models, the newly developed model predicted signal loss with the greatest accuracy as it gives the lowest root-mean-square error. The newly developed model is very efficient for signal propagation and path loss prediction.

Fuzz-classification(p,l)-Angel:An enhanced hybrid artificial intelligence based fuzzy logic for multiple sensitive attributes against privacy breaches

The inability of traditional privacy-preserving models to protect multiple datasets based on sensitive attributes has prompted researchers to propose models such as SLOMS,SLAMSA,(p,k)-Angelization,and(p,l)-Angelization,but these were found to be insufficient in terms of robust privacy and performance.(p,l)-Angelization was successful against different privacy disclosures,but it was not efficient.To the best of our knowledge,no robust privacy model based on fuzzy logic has been proposed to protect the privacy of sensitive attributes with multiple records.In this paper,we suggest an improved version of(p,l)-Angelization based on a hybrid AI approach and privacy-preserving approach like Generalization.Fuzz-classification(p,l)-Angel uses artificial intelligence based fuzzy logic for classification,a high-dimensional segmentation technique for segmenting quasi-identifiers and multiple sensitive attributes.We demonstrate the feasibility of the proposed solution by modelling and analyzing privacy violations using High-Level Petri Nets.The results of the experiment demonstrate that the proposed approach produces better results in terms of efficiency and utility.

Optimal Tuning of FOPID-Like Fuzzy Controller for High-Performance Fractional-Order Systems

This paper addresses improvements in fractional order(FO)system performance.Although the classical proportional-integral-derivative(PID)-like fuzzy controller can provide adequate results for both transient and steady-state responses in both linear and nonlinear systems,the FOPID fuzzy controller has been proven to provide better results.This high performance was obtained thanks to the combinative benefits of FO and fuzzy-logic techniques.This paper describes how the optimal gains and FO parameters of the FOPID controller were obtained by the use of a modern optimizer,social spider optimization,in order to improve the response of fractional dynamical systems.This group of systems had usually produced multimodal error surfaces/functions that occasionally had many variant local minima.The integral time of absolute error(ITAE)used in this study was the error function.The results showed that the strategy adopted produced superior performance regarding the lowest ITAE value.It reached a value of 88.22 while the best value obtained in previous work was 98.87.A further comparison between the current work and previous studies concerning transient-analysis factors of the model’s response showed that the strategy proposed was the only one that was able to produce fast rise time,low-percentage overshoot,and very small steady-state error.However,the other strategies were good for one factor,but not for the others.

Fuzzy logic based coordinated control of battery energy storage system and dispatchable distributed generation for microgrid

Microgrid is a good option to integrate renewableenergy sources (RES) into power systems. Inorder to deal with the intermittent characteristics of therenewable energy based distributed generation (DG) units,a fuzzy-logic based coordinated control strategy of a batteryenergy storage system (BESS) and dispatchable DGunits is proposed for the microgrid management system(MMS). In the proposed coordinated control strategy, theBESS is used to minimize active power exchange at thepoint of common coupling of the microgrid for grid-connectedoperation, and is used for frequency control for islandoperation. The efficiency of the proposed controlstrategy was tested by case studies using DIgSILENT/PowerFactroy.