A graphical tuning of PI^λ controllers for fractional-delay systems

This article provides a graphical parameter tuning method of PIλ controllers for fractional-order time-delay systems. First, the complete stabilizing region of PIλ controller in proportional-integral plane, for a fixed λ, is determined in terms of a graphical stability criterion applicable to fractional-delay systems. Then, the stabilizing region is maximized analytically with respect to parameter λ to expect the most various behaviors of the closed-loop systems. Finally, by defining appropriate functions relative to the requirements of gain and phase margins, the curves in the maximized stabilizing region satisfying the pre-specified gain and phase margins are drawn, which releases a flexible parameter tuning procedure. Numerical examples are given to illustrate the design steps.     

Automatic design of fuzzy logic controllers for medium access control in wireless body area networks – An evolutionary approach

Soft computing techniques including fuzzy logic have been successfully applied to wireless body area networks (WBANs). However, most of the existing research works rely on manual design of the fuzzy logic controller (FLC). To address this issue, in this paper, we propose an evolutionary approach to automate the design of FLCs for cross layer medium access control in WBANs. With the goal of improving network reliability while keeping the communication delay at a low level, we have particularly studied the usefulness of three coding schemes with different levels of flexibility during the evolutionary design process. The influence of fitness functions that measure the effectiveness of each possible FLC design has also been examined carefully in order to achieve a good balance between reliability and performance. Moreover, we have utilised surrogate models to improve the efficiency of the design process. In consideration of practical usefulness, we have further identified two main design targets. The first target is to design effective FLCs for a specific network configuration. The second target focuses on designing FLCs to function across a wide range of network settings. In order to examine the usefulness of our design approach, we have utilised two widely used evolutionary algorithms, i.e. particle swarm optimisation (PSO) and differential evolution (DE). The FLC designed by our approach is also shown to outperform some related algorithms as well as the IEEE 802.15.4 standard.     

A simple and effective evolutionary algorithm for the capacitated location–routing problem

This paper proposes a hybrid genetic algorithm (GA) to solve the capacitated location–routing problem. The proposed algorithm follows the standard GA framework using local search procedures in the mutation phase. Computational evaluation was carried out on three sets of benchmark instances from the literature. Results show that, although relatively simple, the proposed algorithm is effective, providing competitive results for benchmark instances within reasonable computing time.     

Optimization of process parameters through fuzzy logic and genetic algorithm – A case study in a process industry

The simultaneous generation of steam and power, which is commonly referred to as cogeneration, has been adopted by many sugar mills in India to overcome the power shortage. It becomes an increasingly important source of income for sugar factories. The problems faced by the sugar mill industry arise mainly due to failures of either the complete system or some specific components during the cogeneration process. This paper presents the failure analysis of the boiler during the cogeneration process and provides solution to overcome these failures. The failures frequently occur in the screw conveyor and in the drum feeder of fuel feeding system and the grate of the boiler. In this research work, the statistical tools viz., Failure Mode and Effect Analysis (FMEA) and the Taguchi method have been applied to investigate and alleviate these failures. Since conventional FMEA has some limitations and Taguchi method does not give better solution, fuzzy FMEA has been employed to overcome the limitations and genetic algorithm technique has been applied to obtain failure – free system during the cogeneration process.     

Synthesis of fuzzy logic and Dempster–Shafer Theory for the simulation of the decision-making process in stock trading systems

Modern computerized stock trading systems (mechanical trading systems) are based on the simulation of the decision-making process and generate advice for traders to buy or sell stocks or other financial tools by taking into account the price history, technical analysis indicators, accepted rules of trading and so on. Two stock trading simulating systems based on trading rules defined using fuzzy logic are developed and compared. The first is based on the so-called “Logic-Motivated Fuzzy Logic Operators” (LMFL) approach and aims to avoid certain disadvantages of the classical Mamdani’s method, which has been developed for use in fuzzy logic controllers and not for solving the decision-making problems of stock trading. The LMFL   approach is based on the modified mathematical representation of t$t$-norm and Yager’s implication rule. The second trading system combines the tools of fuzzy logic and Dempster–Shafer Theory (DST  ) to represent the features of the decision-making process more transparently. The fuzzy representation of trading rules based on the theory of technical analysis is used in these expert systems. Since the theory of technical analysis is based on the indicators used by experts to predict stock price movements, the method maps these indicators into new inputs that can be used in a fuzzy logic system. The only required inputs to calculate these indicators are past sequences (history) of stock prices. The method relies on fuzzy logic to choose an appropriate decision when certain price movements or certain price formations occur. The optimization procedure based on historical (teaching) data is used as it significantly improves the performance of such expert systems. The efficiency of the developed expert systems is measured by comparing their outputs versus stock price movements. The results obtained using real NYSE$NYSE$ data allow us to say that the developed expert system based on the synthesis of fuzzy logic and DST provides better results and is more reliable. Moreover, such a conjunction of fuzzy logic, DST and technical analysis, makes it possible to make a profit even when trading against a dominating trend.     

A new metric for L–R fuzzy numbers and its application in fuzzy linear systems

In this paper, a metric based on modified Euclidean metric on interval numbers, for L–R fuzzy numbers with fixed $L(\cdot)$ and $R(\cdot)$ is introduced. Then, it is applied for solving L–R fuzzy linear system (L–R-FLS) with fuzzy right-hand side, so that L–R-FLS is transformed to the minimization problem. The solution of the mentioned non-linear programming problem is our favorite fuzzy number vector solution. Two constructive Algorithms are proposed in detail and the method is illustrated by solving several numerical examples.     

Hybrid laser pointer detection algorithm based on template matching and fuzzy rule-based systems for domotic control in?real?home environments

A fundamental problem for disabled or elderly people is to manage their homes while carrying out an almost normal life, which implies using and interacting with a number of home devices. Recent studies in smart homes have proposed methods to use a laser pointer for interacting with home devices, which represents a more user-friendly and less expensive home device control environment. However, detecting the laser spot on the original non-filtered images, using standard and non-expensive cameras, and considering real home environments with varying conditions, is currently an open problem.     

A technical note on the paper “hGA: Hybrid genetic algorithm in fuzzy rule-based classification systems for high-dimensional problems”

This paper provides a corrected formulation to the mixed integer programming model proposed by Aydogan et al. (2012) [1]. They proposed a genetic algorithm to learn fuzzy rules for a fuzzy rule-based classification system and developed a Mixed Integer Programming model (MIP) to prune the generated rules by selecting the best set of rules to maximize predictive accuracy. However, their proposed MIP formulation contains errors, which are described in this technical note. We develop corrections and improvements to the original formulation and test it with non-parametric statistical tests on the same data sets used to evaluate the original model. The statistical analysis shows that the results of the correction formulation are significantly different from the original model.     

A proposal for future data organization in enterprise systems—an analysis of established database approaches

The digital transformation sets new requirements to all classes of enterprise systems in companies. ERP systems in particular, which represent the dominant class of enterprise systems, are struggling to meet the new requirements at all levels of the architecture. Therefore, there is an urgent need to reconsider the overall architecture of the systems and address the root of the related issues. Given that many restrictions ERP pose on their adaptability are related to the standardization of data, the database layer of ERP systems is addressed. Since database serve as the foundation for data storage and retrieval, they limit the flexibility of enterprise systems and the chance to adapt to new requirements accordingly. So far, relational databases are widely used. Using a systematic literature approach, recent requirements for ERP systems were identified. Prominent database approaches were assessed against the 23 requirements identified. The results reveal the strengths and weaknesses of recent database approaches. To this end, the results highlight the demand to combine multiple database approaches to fulfill recent business requirements. From a conceptual point of view, this paper supports the idea of federated databases which are interoperable to fulfill future requirements and support business operation. This research forms the basis for renewal of the current generation of ERP systems and proposes to ERP vendors to use different database concepts in the future.

     

Probing the axioms of evolutionary algorithm design: Commentary on “On the mapping of genotype to phenotype in evolutionary algorithms” by Peter A. Whigham,Grant Dick,and James Maclaurin

Properties such as continuity, locality, and modularity may seem necessary when designing representations and variation operators for evolutionary algorithms, but a closer look at what happens when evolutionary algorithms perform well reveals counterexamples to such schemes. Moreover, these variational properties can themselves evolve in sufficiently complex open-ended systems. These properties of evolutionary algorithms remain very much open questions.     

Codes of conduct in Open Source Software—for warm and fuzzy feelings or equality in community?

Software Quality Journal - This paper focuses on codes of conduct (CoC) of Free and Open Source Software (F/OSS) and their role in improving women’s participation in online communities of...     

Commentary on “A new generalized improved score function of interval-valued intuitionistic fuzzy sets and applications in expert systems”

In this paper, we demonstrate that the Theorem 3.1 in a recently published paper by Garg [Appl. Soft Comput. 38 (2016) 988–999] is incorrect by a counterexample. Further, we point out the shortcomings of Garg's proposed generalized improved score function for practical decision making.     

A novel dispersal algorithm in individual-based,spatially-explicit Population Viability Analysis: A new role for genetic measures in model testing?

We describe a new population viability tool: Spatial PVA. Spatial PVA is an individual-based spatially-explicit PVA application which employs a novel stochastic dispersal algorithm that models how animals move through habitat patches. It also includes a non-random breeding algorithm that simulates pedigrees and inbreeding depression. The model repeatedly steps through annual cycles of chance environmental, dispersal and demographic events for a specified time period. We provide a case study to demonstrate how one can compare simulated kinship coefficients with sampled genetic data to test model assumptions and inputs. We also provide a translocation example for an Australian rangelands species, the Yellow-footed Rock-wallaby (Petrogale xanthopus xanthopus).     

A parallel O(log n) algorithm for the drawing of algebraic curves in an n × n square

A parallel O(log n) algorithm for the drawing of algebraic curves in the digital plane is described. The algorithm contains a systolic subroutine and is implemented in a parallel computer structure called pyramid cellular automaton (PCA). The constructibility of conics and especially of circles (Sakoda's (1981) circle problem) in O(log n) time follows as a special case.     

Is neglected heterogeneity really an issue in binary and fractional regression models? A simulation exercise for logit, probit and loglog models

Theoretical and simulation analysis is performed to examine whether unobserved heterogeneity independent of the included regressors is really an issue in logit, probit and loglog models with both binary and fractional data. It is found that unobserved heterogeneity has the following effects. First, it produces an attenuation bias in the estimation of regression coefficients. Second, although it is innocuous for logit estimation of average sample partial effects, it may generate biased estimation of those effects in the probit and loglog models. Third, it has much more deleterious effects on the estimation of population partial effects. Fourth, it is only for logit models that it does not substantially affect the prediction of outcomes. Fifth, it is innocuous for the size of Wald tests for the significance of observed regressors but, in small samples, it substantially reduces their power.     

On an algorithm determining direct superclasses in Java and similar languages with inner classes—Its correctness,completeness and uniqueness of solutions

Some object oriented programming languages allow inner classes. All of them admit inheritance. This combination of inner classes and inheritance is very fruitful however less known. On the other hand it creates a serious problem: how to determine the direct superclass of a given class C, i.e. the class which class C directly inherits from. For there may be several classes of the same name in one program. A specification of the problem and a non-deterministic algorithm are provided. We prove that the algorithm is correct w.r.t. the specification and complete, i.e. if the algorithm signals an error then no solution exists. We show that the specification itself has at most one solution, in other words, it is a complete specification. This proves also that the corresponding parts of Java Language Specification are consistent and define uniquely a fragment of Java semantics.     

Do air pollution emissions and fuel consumption models for roadways include the effects of congestion in the roadway traffic flow?

Road transport emission and fuel consumption models are currently used extensively to predict levels of air pollution along roadway links and networks. This paper examines how, and to what extent, models which are currently used to predict emissions and fuel consumption from road traffic include the effects of congestion. A classification framework is presented in which a key factor, driving pattern, connects emissions to congestion. Prediction of the effects of different driving patterns in emission models is generally restricted to certain aspects of modelling, i.e. hot-running emissions of regulated pollutants. As a consequence, the effects of congestion are only partially incorporated in the predictions. The majority of emission models explicitly incorporate congestion in the modelling process, but for one important family of emission models, namely average speed models, this could not be determined directly. Re-examination of the (light-duty) driving patterns on which three average speed models (COPERT, MOBILE, EMFAC) are based, shows that it is likely that congestion is represented in these patterns. Since (hot-running) emission factors are based on these patterns, this implies that the emission factors used in these emission models also reflect different levels of congestion. Congestion is thus indirectly incorporated in these models. It is recommended, that, in order to get more accurate (local) emission predictions and to achieve correct application in particular situations, it is important to improve current average speed models by including a congestion algorithm, or alternatively, at least provide information on the level of congestion in the driving patterns on which these models are based and recommendations on what applications the models are suitable for.     

Distilling the salient features of natural systems: Commentary on “On the mapping of genotype to phenotype in evolutionary algorithms” by Whigham,Dick and Maclaurin

Here we comment on the article, “On the mapping of genotype to phenotype in evolutionary algorithms”, by Peter A. Whigham, Grant Dick, and James Maclaurin. The authors present a critical view on the use of genotype to phenotype mapping in Evolutionary Algorithms, and how the use of this analogy can be detrimental for problem solving. They examine a grammar-based approach to Genetic Programming (GP), Grammatical Evolution (GE), and highlight properties of GE which are detrimental to effective evolutionary search. Rather than use loose analogies and methaphors, we suggest that a focus should be (and has been in GE and other approaches to GP) on addressing one of the most significant open issues in our field, i.e., What are the sufficient set of features in natural, genetic, evolutionary and developmental systems, which can translate into the most effective computational approaches for program synthesis?