International Journal of artificial intelligence research (IJAIR)
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The Comparison of Signature Verification Result Using 2DPCA Method and SSE Method
The rate of speed and validation verify to be a reference of quality information and reliable results. Everyone has signature characteristics but it will be difficult to match original signatures with a clone. Two Dimensional Principal Component Analysis (2DPCA) method, Sum Equal Error (SSE) method includes a method that can provide accurate data verification value of 90% - 98%. Results of scanned signatures, converted from RGB image - grayscale - black white (binary color). The extraction process of each method requires experimental data as a data source in pixel size. Digital image consists of a collection of pixels then each image is converted in a matrix. Preprocessing Method 2 DPCA each data is divided into data planning and data testing. Extraction on SSE method, each data sought histogram value and total black value. This study yields a comparison of the suitability of the extraction results of each method. Both of these methods have a data accuracy rate of 97% - 98%. When compared to the results of the accuracy of image verification with 2DPCA method: SSE is 97%: 96%. With the same data source will be tested result of 2DPCA method with SSE method
A Modified Meta-Heuristic Approach for Vehicle Routing Problem with Simultaneous Pickup and Delivery
The aim of this work is to develop an intelligent optimization software based on enhanced VNS meta-heuristic to tackle Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD). An optimization system developed based on enhanced Variable Neighborhood Search with Perturbation Mechanism and Adaptive Selection Mechanism as the simple but effective optimization approach presented in this work. The solution method composed by combining Perturbation based Variable Neighborhood Search (PVNS) with Adaptive Selection Mechanism (ASM) to control perturbation scheme. Instead of stochastic approach, selection of perturbation scheme used in the algorithm employed an empirical selection based on each perturbation scheme success along the search. The ASM help algorithm to get more diversification degree and jumping from local optimum condition using most successful perturbation scheme empirically in the search process. A comparative analysis with a well-known exact approach is presented to test the solution method in a generated VRPSPD benchmark instance in limited computation time. Then a test to VRPSPD scenario provided by a liquefied petroleum gas distribution company is performed. The test result confirms that solution method present superior performance against exact approach solution in giving best solution for larger sized instance and successfully obtain substantial improvements when compared to the basic VNS and original route planning technique used by a distributor company
Quantum Inspired Genetic Programming Model to Predict Toxicity Degree for Chemical Compounds
Cheminformatics plays a vital role to maintain a large amount of chemical data. A reliable prediction of toxic effects of chemicals in living systems is highly desirable in domains such as cosmetics, drug design, food safety, and manufacturing chemical compounds. Toxicity prediction topic requires several new approaches for knowledge discovery from data to paradigm composite associations between the modules of the chemical compound; such techniques need more computational cost as the number of chemical compounds increases. State-of-the-art prediction methods such as neural network and multi-layer regression that requires either tuning parameters or complex transformations of predictor or outcome variables are not achieving high accuracy results. This paper proposes a Quantum Inspired Genetic Programming “QIGP†model to improve the prediction accuracy. Genetic Programming is utilized to give a linear equation for calculating toxicity degree more accurately. Quantum computing is employed to improve the selection of the best-of-run individuals and handles parsimony pressure to reduce the complexity of the solutions. The results of the internal validation analysis indicated that the QIGP model has the better goodness of fit statistics and significantly outperforms the Neural Network model
Computer Vision and Image Processing: A Paper Review
Computer vision has been studied from many persective. It expands from raw data recording into techniques and ideas combining digital image processing, pattern recognition, machine learning and computer graphics. The wide usage has attracted many scholars to integrate with many disciplines and fields. This paper provide a survey of the recent technologies and theoretical concept explaining the development of computer vision especially related to image processing using different areas of their field application. Computer vision helps scholars to analyze images and video to obtain necessary information,   understand information on events or descriptions, and scenic pattern. It used method of multi-range application domain with massive data analysis. This paper provides contribution of recent development on reviews related to computer vision, image processing, and their related studies. We categorized the computer vision mainstream into four group e.g., image processing, object recognition, and machine learning. We also provide brief explanation on the up-to-date information about the techniques and their performance
Solution Search Simulation The Shortest Step On Chess Horse Using Breadth-First Search Algorithm
Horse seed in the chess board movement resembles the letter L. The chess pieces are one of a very hard-driven beans and seeds are often also the most dangerous if not carefully considered every movement. Simulation of this problem provides a chess board size n x n. Target (goal) of this problem is to move a horse beans of a certain position on a chess board position to the desired destination with the shortest movement simulates all possible solutions to get to the goal position. This problem is also one of the classic problems in artificial intelligence (AI). Settlement of this problem can use the help system and tree production tracking.Therefore, designed a simulation applications by utilizing several techniques of simulation programming and Breadth-First Search method. With this method, all nodes will be traced and the nodes at level n will be visited first before visiting the nodes at level n + 1. The purpose of this study is to design a software that is able to find all the solutions for the shortest movement toward the goal position by using the system of production and tracking tree.Results from this paper is that the software is able to find all solutions shortest movement a horse beans from the initial position to the goal position and displays the simulation of the movement of the horse in the chess board
Application to Determination of Scholarship Worthiness Using Simple Multi Attribute Rating Technique and Merkle Hellman Method
This research was focused on explaining how the concept of simple multi attribute rating technique method in a decision support system based on desktop programming to solve multi-criteria selection problem, especially Scholarship. The Merkle Hellman method is used for securing the results of choices made by the Smart process. The determination of PPA and BBP-PPA scholarship recipients on STMIK Triguna Dharma becomes a problem because it takes a long time in determining the decision. By adopting the SMART method, the application can make decisions quickly and precisely. The expected result of this research is the application can facilitate in overcoming the problems that occur concerning the determination of PPA and BBP-PPA scholarship recipients as well as assisting Student Affairs STMIK Triguna Dharma in making decisions quickly and accuratel
Decision Support System For Election Of Members Unit Patients Pamong Praja
Civil Service Police Unit (municipal police) is part of the area in the enforcement of legislation and arrangements for public order and public tranquility . Decision Support System or DSS ( Decision Support System ) is a computer -based information systems whose main goal is to help decision -making utilize data and models to solve the problems that are unstructured and semi- structured . In accepting prospective members of the previous municipal police PSDM section sorting and selecting applicants one by one entering the data so that the data obtained is not clear didapt results of each participant. By using Fuzzy Multiple Attribute Decision Making (FMADM) is used to find an alternative from a number of alternatives to optimize certain criteria , while the Simple Additive Weighting method (SAW). SAW method is often also known term weighted summation method . The basic concept is to find a method SAW weighted summation of the performance ratings of all the attributes of each alternative
Factors Analysis And Profit Achievement For Trading Company By Using Rough Set Method
This research has been done to analysis the financial raport fortrading company and it is intimately related to some factors which determine the profit of company. The result of this reseach is showed about New Knowledge and perform of the rule. In discussion, by followed data mining process and using Rough Set method. Rough Set is to analyzed the performance of the result. This  reseach will be assist to the manager of company with draw the intactandobjective. Rough set method is also to difined the rule of discovery process and started the formation about Decision System, Equivalence Class, Discernibility Matrix, Discernibility Matrix Modulo D, Reduction and General Rules. Rough set method is efective model about the performing analysis in the company. Keywords : Data Mining, General Rules, Profit,. Rough Set
Application of Smart Bats Algorithm for Optimal Design of Power Stabilizer System at Sengkang Power Plant
The problem of using Power System Stabilizer (PSS) in generator excitation is how to determine the optimal PSS parameter. To overcome these problems, the authors use a method of intelligent bats based algorithm to design PSS. Bat Algorithm is an algorithm that works based on bat behavior in search of food source. Correlation with this research is, food sources sought by bats represent as PSS parameters to be optimized. Bat's algorithm will work based on a specified destination function, namely Integral Time Absolute Error (ITAE). In this research will be seen the deviation of velocity and rotor angle of each generator, in case of disturbance in bakaru generator. The analysis results show that the uncontrolled system produces a large overshoot oscillation, and after the addition of PSS oscillation control equipment can be muted. So that the overshoot and settling time of each generator can be reduced and the generator can quickly go to steady state conditio
Design of the expert system to analyze disease in Plant Teak using Forward Chaining
Teak is one kind of plant that is already widely known and developed by the wider community in the form of plantations and community forests. This is because until now Teak wood is a commodity of luxury, high quality, the price is expensive, and high economic value. Expert systems are a part of the method sciences artificial intelligence to make an application program disease diagnosis teak computerized seek to replace and mimic the reasoning process of an expert or experts in solving the problem specification that can be said to be a duplicate from an expert because science knowledge is stored inside a database Expert System for the diagnosis of disease teak using forward chaining method aims to explore the characteristics shown in the form of questions in order to diagnose the disease teak with web-based software. Device keel expert system can recognize the disease after consulting identity by answering some of the questions presented by the application of expert systems and can infer some kind of disease in plants teak. Data disease known customize rules (rules) are made to match the characteristics of teak disease and provide treatment solutions