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A new method, based on support vector machines (SVMs) and genetic algorithm (GA), is proposed for automatic Intra-Pulse modulation recognition (AIMR). In particular, the best feature subset from the combined pulse descriptor word (PDW) feature set and time-frequency feature set is optimized using genetic algorithm. Compared to the conventional decision-theoretic method, the method proposed avoids...
Efficient utilization of sensor energy to prolong the WSN' lifetime is proposed in this paper. A hybrid PSO Genetic sleep scheduling algorithm for WSNs to escape the local optima trap is the focus of this work. The proposed scheme uses a new parameter: Local Optimum Detector (LOD) for switching from PSO to GA algorithm in order to escape to the local optima trap caused by PSO.
Online transaction failures often show up as "500: Internal Server Error" in web server access logs. In many instances determining the root cause of the failure is a difficult task. It could either be a bug associated with a specific HTTP request alone or the result of an undesirable state created by previous HTTP transactions. The latter case, which we call workload dependent faults, are...
Testing and fixing Web Application Firewalls (WAFs) are two relevant and complementary challenges for security analysts. Automated testing helps to cost-effectively detect vulnerabilities in a WAF by generating effective test cases, i.e., attacks. Once vulnerabilities have been identified, the WAF needs to be fixed by augmenting its rule set to filter attacks without blocking legitimate requests....
The multidimensional assignment problem (MAP) is a natural extension of the well known assignment problem. A problem with s dimensions is called a SAP. The most studied NP-hard case of the MAP is the 3AP. Memetic algorithms have been proven to be the most effective technique to solve MAP. The use of powerful local search heuristics in combination with a genetic algorithm, even if it has a simple structure,...
Human life can be seriously affected by unusual high solar flare. It causes serious problems such as destroying satellites, damaging electric power plants, etc. Predicting solar flare peaks is indispensable. Support Vector Machine (SVM) was used to predict the solar flare intensity based on data of the past. However, such prediction is an extremely difficult imbalanced classification problem causing...
Existing clustering techniques primarily rely on prior knowledge about the data, such as the number of clusters and radii. However, in real applications, the number of clusters and the radii of clusters are usually unknown. Therefore, the performance of clustering methods with overlapping data is degraded due to their limitations in finding all cluster centers with uneven density values. Hence, a...
The hydrothermal coordination can be defined as a problem to determine the optimum usage of the hydroelectric and thermoelectric resources available during a period. In hydrothermal generation systems with a predominance of hydroelectric power plants, like in the Brazilian system, the problem consists in replacing the thermal generation by hydropower generation to minimize the system operational costs...
The self-adaptive sliding mode position controller based on genetic algorithm optimization is designed for the servo motor drive system. Firstly, the self-adaptive sliding mode position controller is researched to estimate the magnitude of the unknown disturbance in the perturbed system. Then, the adaptive genetic algorithm is used to optimize the ideal adaptive parameters and switching parameters...
This paper address the problem of scheduling a set of jobs with non-zero ready times and incompatible job families on a set of identical parallel batch machines so as to minimize the total weighted tardiness. In this problem, each machine can process several jobs of a same family simultaneously as a batch as long as the machine capacity is not exceeded. Jobs of a family has the same processing time...
Industrial equipment, such as bulldozers, excavators, and cranes, requires human operation. Construction machines with better operability are necessary in order to improve productivity. The evaluation of such operational equipment is performed in order to obtain better operability, at the design stage, by sensory evaluation from a specific evaluator. Therefore, the design and evaluation of operational...
The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which has initially been proposed to solve optimization of mathematical test functions with a unique neighbourhood search mechanism. However, this neighbourhood search mechanism could not be directly applied to combinatorial discrete optimization problems. The employed and onlooker bees need to be equipped with problem-specific...
Wavelet neural network has a slow convergence rate, weak global search capability and easy to search the search results to a minimum, while the genetic algorithm has a high degree of parallelism, randomness, adaptive search and global optimization. The wavelet neural network is transformed and transformed to obtain the discretized wavelet neural network. In this paper, the three-layer wavelet neural...
Combinatorial testing is a promising technique for testing highly-configurable systems. Software systems become larger and more complex every day, and due to the time and cost limitations, it is infeasible to test everything in a software with a large configuration space, or a graphical user interface with many settings and events. Combinatorial testing generates an interaction test suite to discover...
In this paper, an open source C++ Genetic Algorithm library is proposed called openGA. This library is capable of optimization in each of single objective, multi-objective and interactive modes. The main motivation for proposing this library is to provide freedom to users for designing their custom solution data model without limitations which many currently available software/libraries suffer from...
QuantMiner, proposed by Salleb-Aouissi et al., is one of the well-known systems for mining quantitative association rules using a genetic algorithm (GA). We have applied the GA-based methods of QuantMiner to multi-relational data mining (MRDM), where mining rules involves multiple relations from a relational database, and our preliminary experiments showed that a straightforward application of QuantMiner...
In the machining process, the rationalization of the cutting amount is an important way to effectively improve the productivity, reduce the cost and improve the quality of the workpiece. The rapid development of genetic algorithm has made remarkable achievements in solving the problem of nonlinear optimization. However, in the process of machining, there are many factors that affect the amount of...
High-performance processors utilize embedded thermal sensors to continuously monitor the temperature of the chip during runtime. However, the overheating locations change temporally and spatially, depending on the various workloads running on the chip. Moreover, on-chip thermal sensor readings are highly affected by noise due to fabrication variations and randomness, which make the task of thermal...
In this paper we present a new control strategy of wind turbine, by controlling the pitch angle that must be regulated to capture the maximum of power using PID controller and particle swarm optimization, the problem is to identify the PID controller parameters employing the PSO technique. This study makes a mathematical model, which is used to control the power characteristics of the turbine, a comparison...
The main purpose of this work is to implement a new and accurate approach based on Time Domain Reflectometry (TDR) combined with Adaptive Neuro-Fuzzy Inference System (ANFIS) to solve the problem of soft faults detection and localization on complex wiring electric network. Firstly, the response of the transmission line is given by applying the Finite Difference Time Domain method (FDTD) on the transmission...
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