• The Transactions of the Korea Information Processing Society
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• v.3 no.7
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• pp.1773-1780
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• 1996

KBANN (knowledge-based artificial neural network) combining the symbolic approach and the numerical approach has been shown to be more effective than other machine learning models. However KBANN doesn't have the theory refinement ability because the topology of network can't be altered dynamically. Although TopGen was proposed to extend the ability of KABNN in this respect, it also had some defects due to the link-ing of hidden nodes to input nodes and the use of beam search. The algorithm which could solve this TopGen's defects, by adding the hidden nodes linked to next layer nodes and using hill-climbing search with backtracking, is designed.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.241-245
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• 1989

A knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. This paper presents an expert system to diagnose the various faults in power system. The developed expert system is represented considering two points; the possibility of solution and the fast processing speed. As uncertainties exist in the facts and rules which comprise the knowledge base of the expert system, Certainty Factor, which is based on the confirmation theory is used for the inexact reasoning. Also, as the diagnosis problem requires the inductive reasoning process in nature, the solution is imperfect and not unique in general. So the expert system is designed to generate all the possible hypothesis in order of the possibility and also it can explain the propagation procedure of the faults for each solution using the built in backtracking mechanism. In realization of the expert system, the processing speed is greatly dependent upon the problem representation, reasoning scheme and search strategy. So, in this paper the fault diagnosis problem itself is analysed from the view point of Artificial Intelligence and as a result, the expert system has the following basic features. 1) The certainty factor is adopted in the inference engine for inexact reasoning. 2) Problem apace is represented using the problem reduction technique. 3) Bidirectional reasoning scheme is used. 4) Best first search strategy is adopted for rapid processing. The expert system was developed us ing PROLOG language.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2780-2785
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• 1997

Although KBANN(knowledge-based artificial neural network) has been shown to be more effective than other machine learning algorithms, KBANN doesn't have the theory refinement capability because the topology of the network can't be altered dynamically. Although TopGen algorithm was proposed to extend the ability of KABNN in this respect, it also had some defects due to the connection of hidden nodes from all input nodes and the use of beam search. An algorithm, which could solve this TopGen's defects by adding the hidden nodes connected from only related input nodes and using hill-climbing search with backtracking, is proposed.

• Journal of applied mathematics & informatics
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• v.29 no.1_2
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• pp.173-190
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• 2011

In this paper, we construct a new approach of affine scaling interior algorithm using the affine scaling conjugate gradient and Lanczos methods for bound constrained nonlinear optimization. We get the iterative direction by solving quadratic model via affine scaling conjugate gradient and Lanczos methods. By using the line search backtracking technique, we will find an acceptable trial step length along this direction which makes the iterate point strictly feasible and the objective function nonmonotonically decreasing. Global convergence and local superlinear convergence rate of the proposed algorithm are established under some reasonable conditions. Finally, we present some numerical results to illustrate the effectiveness of the proposed algorithm.

• IE interfaces
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• v.6 no.2
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• pp.117-131
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• 1993

A job sequencing model is developed and its computer system is tested for processing cold-rolled coils in Tandem Cold Mills(TCM) at the Pohang Iron and Steel Company. Given coils waiting to be processed, this system generates a sequence of jobs satisfying operational constraints for the TCM process. We formulate the problem as a constraint satisfaction problem and employ the backtracking technique combined with looking ahead features in order to generate a feasible solution within a reasonable time. Our system is implemented in C language on 80486-based IBM PC. Some tests based on the real data show that our system is adequate with respect to search time and that it consistantly generates a good feasible solution.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.119-139
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• 2002

In electronic catalogs, each item is represented as an independent unit while the parts of the item can be composed of a higher level of functionality. Thus, the search for this kind of product database is limited to the retrieval of most similar standard commodities. However, many industrial products need to configure optional parts to fulfill the required specifications. Since there are many paths in finding the required specifications, we need to develop a search system via the configuration process. In this system, we adopt a two-phased approach. The first phase finds the most similar template, and the second phase adjusts the template specifications toward the required set of specifications by the Constraint and Rule Satisfaction Problem approach. There is no guarantee that the most similar template can find the most desirable configuration. The search system needs backtracking capability, so the search can stop at a satisfied local optimal satisfaction. This framework is applied to the configuration of computers and peripherals. Template-based reasoning is basically the same as case-based reasoning. The required set of specifications is represented by a list of criteria, and matched with the product specifications to find the closest ones. To measure the distance, we develop a thesaurus of values, which can identify the meaning of numbers, symbols, and words. With this configuration, the performance of the search by configuration algorithm is evaluated in terms of feasibility and admissibility.

• Journal of KIISE
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• v.43 no.10
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• pp.1115-1123
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• 2016

Assumption-based truth maintenance system (ATMS) is a tool that maintains the reasoning process of inference engine. It also supports non-monotonic reasoning based on dependency-directed backtracking. Bookkeeping all the reasoning processes allows it to quickly check and retract beliefs and efficiently provide solutions for problems with large search space. However, the amount of data has been exponentially grown recently, making it impossible to use a single machine for solving large-scale problems. The maintaining process for solving such problems can lead to high computation cost due to large memory overhead. To overcome this drawback, this paper presents an approach towards incrementally maintaining the reasoning process of inference engine on cluster using Spark. It maintains data dependencies such as assumption, label, environment and justification on a cluster of machines in parallel and efficiently updates changes in a large amount of inferred datasets. We deployed the proposed ATMS on a cluster with 5 machines, conducted OWL/RDFS reasoning over University benchmark data (LUBM) and evaluated our system in terms of its performance and functionalities such as assertion, explanation and retraction. In our experiments, the proposed system performed the operations in a reasonably short period of time for over 80GB inferred LUBM2000 dataset.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.96-100
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• 2004

In the ship building industry various problems of erection is counterfeited due to formation of bottle necks in the block erection flow pattern This kind of problems cause accumulated problems in real-time erection right on the floor, When such a problem is approached, a support data of the entire erection sequence should be available, Here planning is done by reasoning about the future events in order to verify the existence of a reasonable series of actions to accomplish a goal. This technique helps in achieving benefits like handling search complications, in resolving goal conflicts and anticipation of bottleneck formation well in advance to take necessary countermeasures and boosts the decision support system, The data is being evaluated and an anticipatory function is to be developed This function is quite relevant in day to day planning operation. The system updates database with rearrangement of off-critical blocks in the erection sequence diagram, As a result of such a system, planners can foresee months ahead and can effectively make decisions regarding the control of loads on the man, machine and work flow pattern, culminating to an efficient load management. Such a foreseeing concept helps us in eliminating backtracking related adjustment which is less efficient compared to the look-ahead concept. An attempt is made to develop a computer program to update the database of block arrangement pattern based on heuristic formulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3B
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• pp.339-348
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• 2004

Packet classification is an important factor to support various services such as QoS guarantee and VPN for users in Internet. Packet classification is a searching process for best matching rule on rule tables by employing multi-field such as source address, protocol, and port number as well as destination address in If header. In this paper, we propose hardware based packet classification algorithm by employing tree bitmap of multi-bit trio. We divided prefixes of searching fields and rule into multi-bit stride, and perform a rule searching with multi-bit of fixed size. The proposed scheme can reduce the access times taking for rule search by employing indexing key in a fixed size of upper bits of rule prefixes. We also employ a marker prefixes in order to remove backtracking during searching a rule. In this paper, we generate two dimensional random rule set of source address and destination address using routing tables provided by IPMA Project, and compare its memory usages and performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.125-132
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• 2023

To NP-complete 3-SAT problem, this paper proposes a O(nm) polynomial time algorithm, where n is the number of literals and m is the total frequency of all literals in equation f. Conventionally well-known DPLLs should perform O(2^𝑙) in the worst case by performing backtracking if they fail to find a solution in a brute-force search of a branch-and-bound for the number of literals 𝑙. DPLL forms the core of the SAT Solver by substituting true(T) or false(F) for a literal so that a clause containing the least frequency literal is true(T) and removing a clause containing that literal. Contrary to DPLL, the proposed algorithm selects a literal _max𝑙 with the maximum frequency and sets $_{\max}({\mid}l{\mid},{\mid}{\bar{l}}{\mid})=1$. It then deletes 𝑙∈c_i clause in addition to ${\bar{l}}$ from ${\bar{l}}{\in}c_i$ clause. Its test results on various k-SAT problems not only show that it performs less than existing DPLL algorithm, but prove its simplicity in satisfiability verification.