searching algorithms
Title: Comparative Analysis of Various Uninformed Searching Algorithms in AI
... search algorithms can be classified into two ...search algorithms such as, Depth First Search (DFS), Breadth First Search (BFS), Iterative Deepening Search (IDS), Uniform Cost Search (UCS) and Depth Limit ...
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Space Searching Algorithms Used by Fungi
... for searching the space available in micro-confined networks, ...informed algorithms, such as A*, this under-performance does not increase importantly with the increase of the size of the ...space ...
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Performance Analysis of Searching Algorithms in C#
... different searching algorithms such as linear search, Binary search and brute force search which are measured in term of time complexity ...of searching algorithm. We have used all above mentioned ...
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A Comparative Study of Sorting and Searching Algorithms
... sorting algorithms enclose its own method for solving the worst, average and best positions based upon the inputs along with the space used and gives an idea that more than one algorithms can be used for ...
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IJCSMC, Vol. 3, Issue. 7, July 2014, pg.751 – 758 RESEARCH ARTICLE A Comparison and Selection on Basic Type of Searching Algorithm in Data Structure
... of searching algorithms and their example. Searching is the process to finding to location of The given data elements in the data ...the searching algorithm on the basis of various factors ...
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A Theoretical Approach Towards Dealing With Planning And Searching In Automated Designing Systems
... and searching algorithms which are specially designed and developed for automated designed ...These algorithms may be characterized as a systematic search which works through a range of possible ...
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A COMPARATIVE STUDY AND ANALYSIS OF SEARCHING AND SORTING ALGORITHMS
... Data-driven algorithms especially use sorting to gain an efficient access to ...sorting algorithms with distinct properties for different architectures have been ...developed. Searching for items and ...
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THE TRANSITION FROM 4G TO 5G BY EMPLOYING FEMTO CELLS PROVEN THROUGH DATA RATE, PLR AND DELAY
... Parallel searching algorithms are then implemented in view of multicore ...parallel searching algorithms are tested and investigated in SGEMM GPU Kernel performance dataset with 241600 records ...
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ASCII based Technique of Obtaining Data Set to Perform Fuzzy Keyword Searching
... say; searching on cloud is still not typo ...type searching algorithms and provide a completely innovative and more effectual method that aims at making searching typo friendly and efficient ...
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S-Hadoop -An enhancement of H2 HadoopShruti Satpute, Shalaka Zaware, Ganesh Phapale, Shubham Shahane
... Abstract: Cloud Computing supports Hadoop framework to process Big Data in parallel. Hadoop has certain limitations that could be exploited to execute the job efficiently. These limitations are mostly because of data ...
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Ichnowski_unc_0153D_18525.pdf
... present algorithms for a robot and a computer in the cloud that allow a robot to effectively utilize the cloud in order to dramatically improve its capabilities when operating in a dynamic ...
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Predicting B L E P T Performance of Unit Earners using Supervised Classification Algorithms
... classification algorithms that could help the examinees identify their chance to pass the licensure exam based on their ...classification algorithms to have a more logical structure for solving the ...These ...
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Review of Apriori Based Algorithms on Mapreduce Framework In Big Data
... ABSTRACT— Frequent pattern Mining is an important discovery in data mining tasks.Thus, it has been the subject of numerous studies and research since its concept came . Mostly studies find all the frequent patterns from ...
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Using Tags for Measuring the Semantic Similarity of Users to Enhance Collaborative Filtering Recommender Systems
... two algorithms to incorporate social tagging and web searching into CF, called SocialSimRank (SSR), used to calculate the similarity between tags and web queries), and SocialPageRank (SPR), used to tabulate ...
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Meta Learning for Graph Neural Networks
... Neural networks can successfully execute challenging tasks when provided with abundant data along with sizable computational resources. Convolutional Neural Networks (CNNs) have broken traditional computer vision ...
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Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA
... Auto-WEKA 1 addresses this problem by treating all of WEKA as a single, highly para- metric machine learning framework, and using Bayesian optimization to find a strong instan- tiation for a given dataset. Specifically, ...
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A Fast Sphere Decoding Algorithm for Space-Frequency Block Codes
... Based on the above results, we can make several observa- tions. First, using sphere decoding, the computational com- plexity of the SF decoder can be reduced by orders of magni- tude without perceptible performance loss ...
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Title: A Novel Approach of Color Histogram Based Image Search/Retrieval
... After getting a query it’s important to extract the features of images, because using these extracting features of input image match with this to our existing images features. The feature is defined as a function of one ...
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PERFORMANCE OF SEPARATED RANDOM USER SCHEDULING (SRUS) AND JOUNT USER SCHEDULING (JUS) IN THE LONG TERM EVOLUTION ADVANCED
... The displayed data are adjusted to standardize existing in previous research because this research is the development of the research. This study is divided into two parts, such as collecting the data which is grabed ...
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“A COMPARATIVE ANALYSIS ON WEB CLUSTERING ALGORITHMS” is to identify the efficient web document clustering algorithm for searching the information
... CLUSTERING ALGORITHMS” is to identify the efficient web document clustering algorithm for searching the information from very large databases available in the web efficiently and ...clustering ...
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