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Essential image processing and analysis tasks, such as image segmentation, simplification and denoising, can be conducted in a unified way by minimizing the Mumford-Shah (MS) functional. Although seductive, this minimization is in practice difficult because it requires to jointly define a sharp set of contours and a smooth version of the initial image. For this reason, various relaxations of the original...
Testing of safety-critical embedded systems is an important and costly endeavor. To date researchers and practitioners have been mainly focusing on the design and application of diverse testing strategies, but leaving the test stopping criteria as an ad hoc decision and an open research issue. In our previous work, we proposed a convergence algorithm that informs the tester when the current testing...
This paper proposes to revisit the 2-D Variational Mode Decomposition (2-D-VMD) in order to separate the incident and reflected waves in experimental images of internal waves velocity field. 2-D-VMD aims at splitting an image into a sequence of oscillating components which are centered around specific spatial frequencies. In this work we develop a proximal algorithm with local convergence guarantees,...
Open source Development Model Algorithm (ODMA) is one of the recently proposed heuristic algorithms that is inspired by open source software development mechanism and community's behaviors. The superior performance of this algorithm has been proven among the other most well-known algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO). However, the original version of this...
Gravitational Search Algorithm (GSA) is a population-based optimization algorithm based on Newton's law of gravity and the notion of mass interactions. GSA has the advantage of proper global search ability. However, it suffers from weak local search due to relatively big step-size of agents in the search process. In order to improve the balance between exploration and exploitation of GSA, two mechanisms...
Optimizing the use of copper especially in the distribution system not only reduces the cost but more importantly lowers the copper losses. This paper presents a unique innovative technique which reduces copper volume while enabling home automation. This model of smart home is designed to provide a base for Smart Grid's functions like demand side management, AMR, load shedding etc. The optimization...
There are many factors affect the stability of reservoir slopes, each of them is associated and coupled with others. Generally, the analysis of slopes stability can be achieved by the method of effect-factors analogy and cluster analysis. Traditional cluster analysis is difficult to obtain the stable global optimal solution, since the results are sensitive to the initial cluster center and the order...
This paper presents a novel approach to stabilize video sequences based on low-rank matrix decomposition. Compared to previous methods which are based on simplified models, our stabilization system can work in situations where significant depth variations exist in the scenes and the camera undergoes large translational movement. We formulate the stabilized frames as a low-rank matrix. This allows...
The artificial bee colony algorithm is a swarm intelligence optimization algorithm inspired by the intelligent foraging behavior of honeybees. In this paper, modified ABC algorithms are proposed for numerical optimization. We have compared the performance of our ABC approach against the basic ABC algorithm, results show that the proposed methods have somewhat improved the convergence rate and global...
A new method of path planning approach to moving robot 2 soccer in dynamic environment based on ant colony algorithm is presented in this paper. For the path planning, a method of adaptive refresh strategy is used to plan the best path, two simplified and perfect probability function and fusion function are derived for the adaptive refresh to optimize the path of obstacle 2 avoiding for Robot 2 soccer...
Planning of the mobile robot is one of the core research areas which is complex, binding and non-linear. Ant colony algorithm is an intelligent optimization algorithm developed in recent years. Aiming at the problems of the ant colony algorithm such as slow convergence speed and long computation cycle, in order to improve the efficiency of route planning, proposed using improved ant colony algorithm...
A computationally efficient methodology is proposed to solve infinite horizon intertemporal optimization problem which appears in the areas of management and economics. Such a problem involves local instability emerging from the interaction of the discount rate in future. An algorithm based on modal space reduction and state parameterization is designed which approximates the performance functional...
Conjugate gradient methods are well known and popular in unconstrained optimization. Numerous studies and modifications have been devoted by researchers to improve this method. In this paper, we introduced a new conjugate gradient coefficient (βk) and tested its performance using exact line search. Numerical results based on number of iterations have shown our new βk performance is better or equivalent...
Taizhou medical city exhibition Center project first adopts channel curtain wall structure, with a beautiful shape, tilt angle and high technology, which solves the key technical design problems of uneven distribution of internal forces in steel skeleton system and large local deformation. On the premise of the comprehensive analysis of several different load combination, irregular geometric space...
After studying the disadvantage of BP neural network which has low convergent speed and trap into local minima easily, an idea of designing a new hybrid neural network model. By using Artificial Bee Colony Algorithm (ABC) to expand the updated space of weight and using the fitness functions to decide the better weight. On the basis, make the acquired better value as the weight of BP neural network...
In contrast, there exist bullwhip effect in the supply chain of perishable product more easily. We establish a system dynamics model of the supply chain of perishable product, analyzing the causes of the bullwhip effects. Analysis shows that the changes of consumer demand, the differences of retailer's order cycle, wholesaler's order cycle, production cycle, the delivery delay of wholesaler and delivery...
A common practical problem when implementing signal model-fitting procedures is that of the frequency local minima. Unfortunately, conventional optimization methods, like Steepest Descent, Newton's Method and Conjugate Gradients (CG) are subject to this problem. What is worse, if the estimated frequency is not correct, the estimated signal amplitude and decay rate will be incorrect. In this paper,...
The interior-point filter algorithm (IPFA) is based on a primal-dual interior-point algorithm with a filter set which can be updated after every iteration, and the algorithm will not cycle between two points that alternately decrease the constraint violation and the barrier objective function. The simulation results from IEEE 30-bus system, IEEE 57-bus system and IEEE 118-bus system show that using...
This paper proposes an optimization method for digital maximum power point tracking (DMPPT), based on a Modified Regula Falsi Method (MRFM). An overview of this method applied to photovoltaic (PV) applications is presented, and its advantages with respect to other optimization methods for MPP applications are commented. The analysis shows that, when compared to other commonly used DMPPT methods such...
We consider the stochastic optimization of a noisy convex loss function defined on p-dimensional grid of points in Euclidean space. We introduce the middle point discrete simultaneous perturbation stochastic approximation (DSPSA) algorithm to this discrete space. Consistent with other stochastic approximation methods, this method formally accommodates noisy measurements of the loss function.
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