Heuristic Function
Load Balancing Technique in Public Cloud Environments using Combination of Heuristic Function and KNN Classification
... The proper utilization of virtual machine in cloud computing environments, manage the process of load. The process of load balancing increases the efficiency and utility of cloud environments. The major components for ...
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Optimization of wireless sensor networks routing protocol based on genetic ant colony algorithm
... the heuristic function, information update strategy, crossover, and selection strategy to optimize the solution value, to a certain extent, inhibit the phenomenon of premature convergence and improve the ...
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AINN ICT4101 FS
... state is a "black box“ – any data structure that supports successor function, heuristic function, and goal test state is defined by variables Xi with values from domain Di goal test is a[r] ...
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Path Planning of Mobile Robot Using Optimized ACA
... a heuristic function and the way to update pheromone so that it can get the global optimal path in different complexity of environments, improves the search speed of the algorithm, and accelerates the ...
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A Cost sensitive Decision Tree Optimized Algorithm Based on Adaptive Mechanism
... Design of the Cost-sensitive Decision Tree Algorithm Based on Adaptive Mechanism Determination of Optimal Heuristic Function In this paper, the heuristic function of CS-C4.5 is improved [r] ...
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Building Trust for Web Services Security Patterns
... of heuristic to evaluate the parameters and estimate the criteria rank for each and every ...of heuristic is the intelligent use of heuristic function ...using heuristic function ...
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A Heuristic Search Algorithm for Flow-Shop Scheduling
... intelligent heuristic search algorithm (IHSA * ) for flow-shop problems with an arbitrary number of jobs and machines and subject to the constraint that the same job sequence is used on each machine has been ...
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SMOKE DETECTION BASED ON IMAGE PROCESSING BY USING GREY AND TRANSPARENCY FEATURES
... ACS-based classification improves on AS- based classification by increasing the significance of exploration the search space toward the high- quality rule. This goal is achieved through an adaptive state transition ...
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Hand Written Character Detection by Using Fuzzy Logic Techniques Kandula Venkata Reddy 1, D. Rajeswara Rao2 , K. Rajesh 3
... active heuristic function similar to the one used by A* search algorithm that adaptively determines the length of the feature vector as well as the features themselves used to classify an input ...
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Energy Optimization in Ad hoc Networks Using Ant Colony Optimization
... In this section, the actual ACO algorithm is modified for energy optimization. The basic idea is to define new heuristic function based on residual energy of node to be visited by the ant packet. Moreover, ...
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Research on Different Heuristics for Minimax Algorithm Insight from Connect 4 Game
... Heuristic function is used in Minimax for evaluation of the current situation of the ...the heuristic function is. Therefore, designing a reasonable heuristic function is pa- ...
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A flaw in a theorem about Schnorr signatures
... has probability at most δ = τ (G)/2 512 ≈ 2 −256 of being invertible under f 00 . So the conversion density is extremely small, yet f 00 still meets the NSWAI condition. Neither the NSWAI condition nor the NSW main ...
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An experimental study of hyper heuristic selection and acceptance mechanism for combinatorial t way test suite generation
... • Membership cardinality, fuzzy rules and normalization – The proposed FIS as the search operator selection and acceptance mechanism is derived from our earlier work on ISR described in [49]. Like ISR, FIS adopts three ...
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A heuristic algorithm for scheduling in a flow shop environment to minimize makespan Pages 173-184 Download PDF
... using heuristic, genetic algorithm (GA), simulated annealing (SA), NEH and Johnson’s algorithm to solve the ...classical heuristic approaches according to effectiveness and performance of ...
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Job shop scheduling with makespan objective: A heuristic approach Pages 273-280 Download PDF
... proposed heuristic, The proposed mode has examined on several well- known benchmarks and the results of the computational experiments are presented (section ...
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Capacity Expansion in Survivable Networks.
... An extensive body of literature exists on capacity design in networks with uncertain demands. For a few please see [7, 8, 9] and [10]. Many branch and bound, stochastic programming, cutting plane and also approximation ...
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A tensor based selection hyper heuristic for cross domain heuristic search
... level heuristic is chosen randomly, if a heuristic per- turbs a solution and consistently generates highly worsening solutions, then such a heuristic is considered as a poor heuristic, causing ...
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Heuristic Evaluation Quality Score (HEQS): A Measure of Heuristic Evaluation Skills
... traditional HE and HE Plus (Chattratichart, and Brodie, 2002), can be compared, and the HEQS scores will identify the better method. A comparison of the two was done by Lindgaard et al. (2004), but they did not take into ...
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Hybrid PSOS Algorithm For Continuous Optimization
... [27] W. Chu, X. Gao, S. Sorooshian, Handling boundary constraints for particle swarm op- timization in high-dimensional search space, Information Sciences 181 (2011) 4569-4581. [28] D. E. Goldberg, Genetic Algorithms in ...
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Meta-heuristic
... Intensification : Exploitation of best found solutions to search thoroughly promising regions of the search space.. Local optimum : An optimal solution within a neighbouring set of solut[r] ...
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