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Precision improvement of the classifiers is one of the main challenges for the Artificial Intelligence researchers. Feature weighting is one of the most common ideas in this area. In this study, in order to increase the accuracy of the K-Nearest Neighbors (KNN) classifier, a nonlinear feature weighting method based on the Spline interpolation is used. In this approach, a unique nonlinear function...
Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above...
Improvements of energy efficiency and reduction of electricity consumption can be promoted by growing knowledge on the determinants of residential electricity consumption level (RECL). Due to numerousness, complexity and multiple correlations among impact factors (IFs) of RECL, feature selection is an essential step to ensure the precision and stability of an explanatory model. However, the current...
Compact evolutionary algorithms (cEAs) are optimization algorithms that require minimal computational cost. They do not require the storage of the population but they represent it by a distribution function. In all known cEAs, normal probability of density function (N-PDF) is used. In this paper, in order to improve the performance of cEAs and to reduce their complicity, we propose a more simple distribution...
This paper introduces a study of the fog computing suitability assessment as a solution for the increasing demand of the IoT devices. In particular, we focus on the energy consumption and the Quality of Service (QoS) as two important metrics of the performance of the fog. Therefore, we present a modeling of these two metrics in the fog. Then, we express the problem as constrained optimization and...
The location of distributed generators (DG) with different size on the power distribution systems could modify the voltage profile and impacts the level of real power losses. Faster optimization technique as well as a high computational speed of load flow are therefore required. This paper presents a linear model and an algorithm that allow to calculate the real power losses of the system. This methodology...
In the Team Orienteering Problem (TOP) a set of locations is given, each with a score. The objective is to determine a fixed number of routes (teams), limited in length, that visit some locations and maximize the sum of the collected scores. For the first time we introduce bi-objective TOP which has a second objective, to balance all team's scores for the purpose of obtaining fair teams. So the second...
Voltage quality is an essential requirement in the operation of electricity distribution systems. At consumer busbars, the deviation from the nominal voltage has specific ranges, prescribed in technical regulations. A widely chosen voltage correction approach is to use reactive power compensation. Capacitor banks are used for this purpose in highly loaded networks, but their placement and sizing require...
Pumping optimization in water distribution networks means to schedule the ON/OFF status of pumps over a typical operating cycle, pursuing the minimum energy cost for pumping and matching technical requirements, e.g. sufficient pressure to satisfy customers' water requests, null water deficit at tanks, avoid complete emptying and overflows of tanks. In aged water distribution networks, pump scheduling...
Diabetes Mellitus is a dreadful disease characterized by increased levels of glucose in the blood, termed as the condition of hyperglycemia. As this disease is prominent among the tropical countries like India, an intense research is being carried out to deliver a machine learning model that could learn from previous patient records in order to deliver smart diagnosis. This research work aims to improve...
Software testing happens to be an inescapable, big-budget and protracted software engineering activity. It is well established that software testing cannot be accomplished in totality even for small input programs. The researchers have been trying to find alternatives like test case selection, minimization, and prioritization. Along with many other approaches, recent research has witnessed the emergence...
Under the framework of South American Council of Infrastructure and Planning (Cosiplan — IIRSA in Spanish) project, related on the management of hazard and risk on regional infrastructure (South America), it is presented a new methodology for the identification of vulnerabilities on the infrastructure and their hazards. The Chilean methodology Management of Risk Disasters at Local level (GRDR in Spanish)...
In recent years, significant research has been conducted on grasp planning for multifingered robot hands. These studies have focused on determining how to obtain suitable grasps from among an infinite number of candidate grasps. This domain's goal is a successful application to unknown environments through the adoption of the extracted grasps. Under difficult conditions, such as grasping a target...
The paper introduces a proposal for an automated magnetic resonance (MR) image segmentation called Case-Based Genetic Algorithm Location-Dependent Image Classification (CBGA-LDIC) and presents its evaluation results. This method finds an appropriate cell set towards efficient image segmentation. It uses location-dependent image classification (LDIC), which is integrated by genetic algorithm (GA) combined...
For text clustering task, distinctive text features selection is important due to feature space high dimensionality. It is essential to reduce the feature space dimension to increase accuracy and decrease processing time. In this work, for text clustering task, we introduce a novel hybrid feature selection model. This method measures the term importance based on the correlation coefficient among four...
This paper introduces a new initialization method of individuals for genetic algorithm (GA) in portfolio optimization problems. In our approach, first a set of assets, variables, composing the portfolio is selected, and then combination of real-valued weights of the portfolio is optimized by GA. In the asset selection, a pairwise asset selection which is an iterative greedy scheme based on the bordered...
One of the most well-known clustering methods for wireless sensor network is, no doubt, the so-called low energy adaptive clustering hierarchy (LEACH) because it is simple and easy to implement. Although LEACH tries to provide a fair selection mechanism by randomly selecting a number of sensors as the cluster-heads, it does not take into account the distribution of sensors, the main reason that LEACH...
In automated test pattern generation (ATPG), test patterns are automatically generated and tested against all specific modeled faults. In this work, three optimization algorithms, namely: genetic algorithm (GA), particle swarm optimization (PSO) and differential evolution (DE), were studied for the purpose of generating optimized test sequence sets. Furthermore, this paper investigated the broad use...
The Demand Response (DR) program is used by public electric utilities to encourage consumers to change their consumption profiles in order to improve the reliability and efficiency of the electric power system (EPS). However, operational particularities due to different categories of residential appliances, consumer satisfaction and comfort are not usually taken into consideration when designing a...
Group role assignment (GRA) with flexible formation (called GRAFF) is a complex problem. The solution with GRA-Based on Exhaustive Search (GRA-ES) is too complex to be practical and the solution with Linear Programming-Based Algorithm (LPBA), implementing by Matlab and IBM ILOG CPLEX package, do not work well when the search space exceeds an extent. This paper proposes a solution to solve GRAFF based...
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