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Differential evolution (DE) algorithm mainly uses the distance and direction information from the current population to guide search. However, it has no mechanism to extract and use global information about the search space. Cloud model is an effective tool in uncertain transforming between qualitative concepts and their quantitative expressions. It can be used to extract the global information about...
Frequent itemsets which are quite useful in many applications always suffer from their huge number and information redundancy. Frequent closed itemsets that provide a minimal and lossless presentation of all frequent itemsets are a solution to the problem. In past years, frequent closed itemsets mining (FCIM) has been extensively studied and many effective FCIM algorithms have been proposed. CHARM...
Differential Evolution (DE) is a numerical optimization approach, which is simple to implement, requires little parameter tuning, and known for remarkable performance. It mainly uses the distance and direction information from the current population to guide its further search. However, it has no mechanism to extract and use global information about the search space. Cloud model is an effective tool...
We propose a novel technique to mine powerful and generalized boolean relations among flip-flops in a sequential circuit for sequential equivalence checking. In contrast to traditional learning methods, our mining algorithm can detect inductive invariants as well as illegal state cubes. These invariants can be arbitrary boolean expressions and can thus prune a large don't care space during equivalence...
This paper presents a new particle swarm optimization based corrective strategy to alleviate overloads of transmission lines. A direct acyclic graph (DAG) technique for selection of participating generators and buses with respect to a contingency is presented. Particle swarm optimization (PSO) technique has been employed for generator rescheduling and/or load shedding problem locally, to restore the...
Combined economic emission dispatch (CEED) involves the simultaneous optimization of fuel cost and emission objectives which are conflicting ones. The bi-objective CEED problem is converted into a single optimization problem by introducing price penalty factor (PPF). A new approach to the reserve constrained CEED based on shuffled frog leaping algorithm (SFLA) is proposed. The algorithm approaches...
This paper presents the application of bio-inspired artificial bee colony (ABC) optimization to constrained economic load dispatch problem. Independent simulations were performed over various systems with different number of generating units having constraints like prohibited operating zones and ramp rate limits. The performance is also compared with other existing similar approaches. The proposed...
Along with the burst of open source projects, software theft (or plagiarism) has become a very serious threat to the healthiness of software industry. Software birthmark, which represents the unique characteristic of a program, can be used for software theft detection. We propose two system call based software birthmarks: SCSSB (system call short sequence birthmark) and IDSCSB (input dependant system...
Ant Colony Optimization (ACO) is more suitable for combinatorial optimization problems. This paper proposes Genetic Evolving Ant Colony Optimization (EACO) method for solving unit commitment (UC) problem. The EACO employs Genetic Algorithm (GA) for finding optimal set of ACO parameters, while ACO solves the UC problem. Problem formulation takes into consideration the minimum up and down time constraints,...
Abstract-A new approach to ORPF (optimal reactive power flow) based on SFLA (shuffled frog leaping algorithm) is proposed. The algorithm approaches to solving ORPF problem are given. By applying the algorithm to dealing with IEEE 30-bus system, compared with the particle swarm optimization (PSO) algorithm and SGA(simple genetic algorithm),the experimental results show that the algorithm is indeed...
The direct design method of optimal diagnostic observer for sampled-data systems is investigated in this paper. Firstly, an appropriate diagnostic observer for sampled-data systems is constructed from the transfer function viewpoint and the dynamics of the discrete time residual with respect to continuous time unknown inputs and faults is derived. Then, the sampled-data fault detection problem is...
The concept of (classical) complete preorder can be characterized in several ways. In previous works we have studied whether complete fuzzy preorders can be characterized by the same properties as in the crisp case. We have proven that this is not usually the case. We have studied five possible characterizations and we have proven that only one still characterizes a fuzzy preorder. In this work we...
In an earlier EPRI project, the authors employed a knowledge-based system (KBS) to develop a tool to guide system operators to restart generators after a blackout. In this paper, the authors convert the KBS formulation into a Mixed Integer Quadratically Constrained Program (MIQCP) problem. Taking advantage of the quasiconcave property of the generation ramping curves, an algorithm to solve the generator...
Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the distributed generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for...
A multi-objective genetic algorithm, based on NSGAII, is implemented to find an optimal condition of minimum voltage deviations, minimum power losses and minimum number of control actions of a transmission network system. The system used as model is an IEEE 30-bus system. Generators and transformers with off-nominal tap ratio are the devices to be controlled. Different probabilities of mutation factors...
We propose a spatial plan generator based on our spatial planning algorithm and spatial growth rules, combine it with evolutionary multi-objective optimization, apply the system to architectural room floor planning, and evaluate its potential as a support tool for planning. We also introduce a framework for combining the architectural room floor planning support system with an interactive evolutionary...
Software component techniques are widely used to enhance productivity and reduce the cost of software systems development. This paper proposes optimization of component connections for a component system that is suitable for embedded systems. This component system adopts a static model that statically instantiates and connects components. The attributes of the components and the interface code for...
Knapsack problem is applied broadly to practice in resource allocation, investment decision-making, storage allocation, loading problem and so on. The paper adopts Handel-C language to program for the simple and improved genetic algorithm that solve knapsack problem. The procedures of the two algorithms are provided in detail in the paper. The improved genetic algorithm enhances obviously global search...
This paper presents a novel optimization approach using improved harmony search (IHS) algorithm to solve economic power dispatch problem. The proposed methodology easily takes care of different equality and inequality constraints of the power dispatch problem to find the optimal solution. To show its efficiency, the proposed algorithm is applied to single area and multi area system of four area having...
In competitive electricity markets, self-scheduling for power producer is a conflicting bi-objective mixed-integer nonlinear optimization problem, where a producer tries to maximize his profit and at the same time, minimizes the risk associated with price forecast uncertainty, while satisfying all the operational constraints. This paper proposes a multi-objective particle swarm optimization (MOPSO)...
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