The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Home energy management (HEM) requires optimization techniques to solve multi-variable and multi-objective problems. The optimal use of energy, the occupants comfort, the reduction of peak power and energy cost are objectives with dissimilar variables behaviors. Their solutions increase in complexity with the number of variables which would be a challenge if the real-time response is needed. Meta-heuristics...
A gene regulatory network reveals the regulatory relationships among genes at a cellular level. The accurate reconstruction of such networks using computational tools, from time series genetic expression data, is crucial to the understanding of the proper functioning of a living organism. Investigations in this domain focused mainly on the identification of as many true regulations as possible. This...
Here, we have proposed a statistical framework based on a novel bat algorithm inspired particle swarm optimisation algorithm for the reconstruction of gene regulatory networks from temporal gene expression data. The recurrent neural network formalism has been implemented to extract the underlying dynamics from time series microarray datasets accurately. The proposed swarm intelligence framework has...
Based on the mobile robot dynamic characteristics of the working environment, this paper presents a model based on classic artificial potential field potential field on the basis of considering dynamic model of velocity potential field, using quantum particle swarm optimization algorithm, using quantum particle swarm optimization algorithm for rapid global search and artificial potential field operations,...
Smart phones are starting to find use in mission critical applications, such as search-and-rescue operations, wherein the mission capabilities are realized by deploying a collaborating set of services across a group of smart phones involved in the mission. Since these missions are deployed in environments where replenishing resources, such as smart phone batteries, is hard, it is necessary to maximize...
A model of RBF neural network (RBFNN) is framed to solve the problem of identification of nonlinear system. In order to realize the structure identification of RBFNN, a kind of hybrid parameter optimization algorithm is proposed based on optimal selection cluster algorithm and PSO. By this algorithm, it is optimally gained the hidden layer node number of RBFNN in terms of input samples. Then the structure...
The secondary structure prediction of RNAs is an important classical problem in bioinformatics. The standard solution is to predict the secondary structure possessing the minimum free energy. In this paper, we propose a fuzzy adaptive particle swarm optimization (FPSO) combining particle swarm optimization (PSO) and fuzzy logic control (FLC) to predict RNA secondary structure with the minimum energy...
This paper proposed a hybrid heuristic algorithm for the integrated large-capacity quay crane scheduling which has two-quay-crane with non-interference constraints, and this model is decomposed into two types of sequencing, i.e. interstage sequencing (hatch sequencing) and intra-stage sequencing (stack sequencing in the same hatch).The stack sequencing problem is solved by a certain reconstructive...
Like many wireless systems, Orthogonal Frequency Division Multiplexing (OFDM) needs proper allocation of limited resources such as total transmit power and available frequency bandwidth among the users to meet their service requirements. In this paper, different versions of two evolutionary approaches, Differential Evolution (DE) and Particle Swarm Optimization (PSO) have been applied for adaptive...
In parallel and distributed systems, optimal task scheduling and load balancing has always been of great interest in order to minimize the time and speed up the process which plays a major role in the efficiency of such systems. By load balancing we mean scheduling the jobs in a way that every job could be executed concurrently while it is mapped to a processing unit, such as a processor (in a multi-processor...
Terrestrial digital broadcasting networks for digital video broadcasting (DVB) systems, such as DVB-T or DVB-T2, can be either multi-frequency (MFN) or single frequency (SFN). Regarding the SFN, the use of the spectrum is more efficient, and receiving locations can be served by several transmitters working at the same frequency. Moreover, DVB receivers based on OFDM modulation schemes can succeed...
This paper introduces a novel adaptation scheme of mutation step size for the Artificial Bee Colony algorithm and compares its results with a number of swarm intelligence and population based optimization algorithms on complex multimodal benchmark problems. The Artificial Bee Colony (ABC) is a swarm based optimization algorithm mimicking the intelligent food foraging behavior of honey bees. The proposed...
Particle swarm optimization (PSO) is simple and efficient, but there is serious premature convergence for solving constrained optimization problem. In order to control premature convergence, this paper proposed dynamic neighborhood hybrid particle swarm optimization (DNH_PSO), which firstly uses the dynamic neighborhood strategy that based on the random topology and the von Neumann topology to improve...
Particle Swarm Optimization (PSO) is a new random computational method for tackling optimization functions. However, it is easily trapped into the local optimum when solving the complexity and high-dimensional problems, which makes the performance of PSO greatly reduced. To overcome this shortcoming, the paper proposes an Improved Particle Swarm Optimization (IPSO), by adding the third particle of...
This paper is concerned with PID controller, which is an extremely important type of controller. However the optimal PID parameters is difficult to determined, their performance are highly sensitive to the initial guess of the solution. An artificial bee colony (ABC) algorithm approach is introduced in PID tuning and on-line tuning as a novel technique for optimum adaptive control in a non-Lyapunov...
Recently Particle Swarm Optimization (PSO) algorithm gained popularity and employed in many engineering applications because of its simplicity and efficiency. The performance of the PSO algorithm can further be improved by using hybrid techniques. There are various hybrid PSO algorithms published in the literature where researchers combine the benefits of PSO with other heuristics algorithms. In this...
This paper presents a heuristic optimization methodology, Bacterial foraging and PSO-DE (BPSO-DE) algorithm by integrating Bacterial foraging optimization Algorithm (BFOA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) for solving Non-Convex Dynamic Economic Dispatch problem (DED). The DED problem exhibits non-convex nature due to valve-point loading effects, ramp rate limits,...
A dynamic clustering algorithm based on hybrid particle swarm-ant colony optimization (PS-ACO) algorithm is presented in the paper. In the algorithm, the number of cluster is dynamic, ACO algorithm is modified by particle swarm optimization (PSO), both the external function and internal function are used to measure the quality evaluation for clustering. The optimal partition is fulfilled by improved...
To solve the problems correlated with fuzzy temporal parameter in real manufacture system, based on trapezoidal fuzzy number, a fuzzy single batch-processing machine with non-identical job sizes (NSBM) model for minimized make span and earliness/tardiness penalties which has fuzzy processing time and fuzzy due date is introduced in this paper firstly. After that, aiming at the problems of easily getting...
In packet-switched computer networks, one of several challenging issues is how to determine an optimal path that satisfies a set of constraints while maintaining high utilization of network resources. This paper proposes an improved particle swarm optimization utilizing Iterative Chaotic Map with Infinite Collapses (ICMIC) perturbations (ICMICPSO) for shortest path computation in computer networks...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.