This book aims at attracting the interest of researchers and practitioners around the applicability of meta-heuristic algorithms to practical scenarios arising from different knowledge disciplines. Emphasis is placed on evolutionary algorithms and swarm intelligence as computational means to efficiently balance the tradeoff between optimality of the produced solutions and the complexity derived from their estimation.
We propose a novel heuristic algorithm for Cube Pruning running in linear time in the beam size. Empirically, we show a gain in running time of a standard machine translation system, at a small loss in accuracy.
A routing algorithm constructs routing tables to forward communication packets based on network status information. Rapid inflation of the Internet increases demand for scalable and adaptive network routing algorithms. Conventional protocols such as the Routing Information Protocol (RIP) (Hedrick, 1988) and the Open Shortest-Path First protocol (OSPF) (Comer, 1995) are not adaptive algorithms; they because they only rely on hop count metrics to calculate shortest paths. In large networks, it is difficult to realize an adaptive algorithm based on conventional approaches. ...
Decoding algorithm is a crucial part in statistical machine translation. We describe a stack decoding algorithm in this paper. We present the hypothesis scoring method and the heuristics used in our algorithm. We report several techniques deployed to improve the performance of the decoder. We also introduce a simplified model to moderate the sparse data problem and to speed up the decoding process. We evaluate and compare these techniques/models in our statistical machine translation system.
This chapter describes the joint application of two soft computing methods – evolutionary algorithms and fuzzy reasoning – to the problem of adaptive distributed routing control in packet-switched communication networks. In this problem, a collection of geographically distributed routing nodes are required to adaptively route data packets so as to minimise mean network packet delay. Nodes reach routing decisions locally using state measurements which are delayed and necessarily only available at discrete sampling intervals. ...
Search algorithms aim to find solutions or objects with specified properties and constraints in a large solution search space or among a collection of objects. A solution can be a set of value assignments to variables that will satisfy the constraints or a sub-structure of a given discrete structure. In addition, there are search algorithms, mostly probabilistic, that are designed for the prospective quantum computer.
This paper presents an approach for Multilingual Document Clustering in comparable corpora. The algorithm is of heuristic nature and it uses as unique evidence for clustering the identiﬁcation of cognate named entities between both sides of the comparable corpora. One of the main advantages of this approach is that it does not depend on bilingual or multilingual resources. However, it depends on the possibility of identifying cognate named entities between the languages used in the corpus.
This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known probabilistic meta-heuristic. It is used to solve discrete and continuous optimization problems. The significant advantage of SA over other solution methods has made it a practical solution method for solving complex optimization problems. Book is consisted of 13 chapters, classified in single and multiple objectives applications and it provides the reader with the knowledge of SA and several applications.
In this tutorial you will gain experience using Cadence Encounter to perform automatic placement
and routing. A place+route tool takes a gate-level netlist as input and rst determines how each
gate should be placed on the chip. It uses several heuristic algorithms to group related gates
together and thus hopefully minimize routing congestion and wire delay. Place+route tools will
focus their eort on minimizing the delay through the critical path. To this end, these tools can
resize gates, insert new buers, and even perform local resynthesis.
Do nhu cầu tính toán vốn có trong việc đưa ra phương pháp phản ứng nhanh hơn, nhiều dấu vết tìm kiếm không phải là hữu ích và chúng ta nên đưa ra các quy tắc tìm kiếm heuristic. Các phản ứng của các cấp độ hoạt động chỉ ra rằng chúng ta chỉ có thể giải quyết vấn đề với một vài biến hoặc một chức năng đơn giản mục tiêu.
Heuristic Search is an important sub-discipline of optimization theory and finds applications in a vast variety of fields, including life science and engineering. Search methods have been useful in solving tough engineering-oriented problems that either could not be solved any other way or solutions take a very long time to be computed. This book explores a variety of applications for search methods and techniques in different fields of electrical engineering.
Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Heuristic Optimal Discrete Bit Allocation Algorithm for Margin Maximization in DMT Systems
Contents Techniques r Introduction to Algorithms r Data Structures and Sorting r Breaking Problems Down r Graph Algorithms r Combinatorial Search and Heuristic Methods r Intractable Problems and Approximations r How to Design Algorithms Resources r A Catalog of Algorithmic Problems r Algorithmic Resources References Index About this document
This book provides an overview of subjects in various fields of life. Authors solve current topics that present high methodical level. This book consists of 13 chapters and collects original and innovative research studies.
Yagle, A.E. “Fast Matrix Computations” Digital Signal Processing Handbook Ed. Vijay K. Madisetti and Douglas B. Williams Boca Raton: CRC Press LLC, 1999
1999 by CRC Press LLC
Fast Matrix Computations
10.1 Introduction 10.2 Divide-and-Conquer Fast Matrix Multiplication
Strassen Algorithm • Divide-and-Conquer • Arbitrary Precision Approximation (APA) Algorithms • Number Theoretic Transform (NTT) Based Algorithms Overview • The Wavelet Transform • Wavelet Representations of Integral Operators • Heuristic Interpretation of Wavelet Sparsiﬁcation
Numerous ATPG algorithms and heuristics have been developed over the years to test digital logic circuits. Some of these methods can trace their origins back to the very beginnings of the digital logic era. Unfortunately, they have proven inadequate to the task.
Since Model Predictive Heuristic Control (MPHC), the earliest algorithm of Model Predictive
Control (MPC), was proposed by French engineer Richalet and his colleagues in 1978, the
explicit background of industrial application has made MPC develop rapidly to satisfy the
increasing request from modern industry. Different from many other control algorithms, the
research history of MPC is originated from application and then expanded to theoretical field,
while ordinary control algorithms often has applications after sufficient theoretical research....
To effectively perform data mining, however, we cannot
naively consider all candidate instantiations, since the
number of such instantiations is exponential in the number
of variables. We provide algorithms and heuristics that ex-
ploit the granularity system and the given constraints to
reduce the hypothesis space for the pattern matching task.
The global approach offers an effective procedure to dis-
cover patterns of events that occur frequently in a sequence
satisfying specific temporal relationships.
We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupervised approach uses a heuristic based on attachment proximity and trains from raw text that is annotated with only part-of-speech tags and morphological base forms, as opposed to attachment information. It is therefore less resource-intensive and more portable than previous corpus-based algorithm proposed for this task. ...