Pub Date : 2014-10-15DOI: 10.4236/JILSA.2014.64015
M. A. Razek
The use of agent technology in a dynamic environment is rapidly growing as one of the powerful technologies and the need to provide the benefits of the Intelligent Information Agent technique to massive open online courses, is very important from various aspects including the rapid growing of MOOCs environments, and the focusing more on static information than on updated information. One of the main problems in such environment is updating the information to the needs of the student who interacts at each moment. Using such technology can ensure more flexible information, lower waste time and hence higher earnings in learning. This paper presents Intelligent Topic-Based Information Agent to offer an updated knowledge including various types of resource for students. Using dominant meaning method, the agent searches the Internet, controls the metadata coming from the Internet, filters and shows them into a categorized content lists. There are two experiments conducted on the Intelligent Topic-Based Information Agent: one measures the improvement in the retrieval effectiveness and the other measures the impact of the agent on the learning. The experiment results indicate that our methodology to expand the query yields a considerable improvement in the retrieval effectiveness in all categories of Google Web Search API. On the other hand, there is a positive impact on the performance of learning session.
{"title":"Dominant Meaning Method for Intelligent Topic-Based Information Agent towards More Flexible MOOCs","authors":"M. A. Razek","doi":"10.4236/JILSA.2014.64015","DOIUrl":"https://doi.org/10.4236/JILSA.2014.64015","url":null,"abstract":"The use of agent technology in a dynamic environment is rapidly growing as one of the powerful technologies and the need to provide the benefits of the Intelligent Information Agent technique to massive open online courses, is very important from various aspects including the rapid growing of MOOCs environments, and the focusing more on static information than on updated information. One of the main problems in such environment is updating the information to the needs of the student who interacts at each moment. Using such technology can ensure more flexible information, lower waste time and hence higher earnings in learning. This paper presents Intelligent Topic-Based Information Agent to offer an updated knowledge including various types of resource for students. Using dominant meaning method, the agent searches the Internet, controls the metadata coming from the Internet, filters and shows them into a categorized content lists. There are two experiments conducted on the Intelligent Topic-Based Information Agent: one measures the improvement in the retrieval effectiveness and the other measures the impact of the agent on the learning. The experiment results indicate that our methodology to expand the query yields a considerable improvement in the retrieval effectiveness in all categories of Google Web Search API. On the other hand, there is a positive impact on the performance of learning session.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-08-11DOI: 10.4236/JILSA.2014.63011
Frerk Saxen, Omer Rashid, A. Al-Hamadi, S. Adler, A. Kernchen, R. Mecke
In this paper, a mobile assistance-system is described which supports users in performing manual working tasks in the context of assembling complex products. The assistance system contains a head-worn display for the visualization of information relevant for the workflow as well as a video camera to acquire the scene. This paper is focused on the interaction of the user with this system and describes work in progress and initial results from an industrial application scenario. We present image-based methods for robust recognition of static and dynamic hand gestures in realtime. These methods are used for an intuitive interaction with the assistance-system. The segmentation of the hand based on color information builds the basis of feature extraction for static and dynamic gestures. For the static gestures, the activation of particular sensitive regions in the camera image by the user’s hand is used for interaction. An HMM classifier is used to extract dynamic gestures depending on motion parameters determined based on the optical flow in the camera image.
{"title":"Image-Based Methods for Interaction with Head-Worn Worker-Assistance Systems","authors":"Frerk Saxen, Omer Rashid, A. Al-Hamadi, S. Adler, A. Kernchen, R. Mecke","doi":"10.4236/JILSA.2014.63011","DOIUrl":"https://doi.org/10.4236/JILSA.2014.63011","url":null,"abstract":"In this paper, a \u0000mobile assistance-system is described which supports users in performing manual \u0000working tasks in the context of assembling complex products. The assistance \u0000system contains a head-worn display for the visualization of information \u0000relevant for the workflow as well as a video camera to acquire the scene. This \u0000paper is focused on the interaction of the user with this system and describes \u0000work in progress and initial results from an industrial application scenario. \u0000We present image-based methods for robust recognition of static and dynamic \u0000hand gestures in realtime. These methods are used for an intuitive \u0000interaction with the assistance-system. The segmentation of the hand based on \u0000color information builds the basis of feature extraction for static and dynamic \u0000gestures. For the static gestures, the activation of particular sensitive \u0000regions in the camera image by the user’s hand is used for interaction. An HMM \u0000classifier is used to extract dynamic gestures depending on motion parameters \u0000determined based on the optical flow in the camera image.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-02DOI: 10.4236/JILSA.2014.62010
Asif Rahman, Siril Yella, M. Dougherty
Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.
{"title":"Simulation Model Using Meta Heuristic Algorithms for Achieving Optimal Arrangement of Storage Bins in a Sawmill Yard","authors":"Asif Rahman, Siril Yella, M. Dougherty","doi":"10.4236/JILSA.2014.62010","DOIUrl":"https://doi.org/10.4236/JILSA.2014.62010","url":null,"abstract":"Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-02DOI: 10.4236/JILSA.2014.62009
G. C. Pereira, L. P. Andrade, R. P. Espíndola, N. Ebecken
The coastal marine habitats are often characterized by high biological activity. Therefore, monitoring programs and conservation plans of coastal environments are needed. So, in order to contribute to decision making process of the Brazilian Information System of Coastal Management, this paper presents a preliminary analysis of the effects of simulated deletions of individual organisms within a planktonic network as knowledge acquisition platform. An in situ scanning flow cytometer was used to data acquisition. A static and undirected food web is generated and represented by a fuzzy graph structure. Our results show through a series of indices the main changes of these networks. It was also verified similar traits and properties with other food webs found in the literature.
{"title":"Structural Analysis and Static Simulation of Coastal Planktonic Networks","authors":"G. C. Pereira, L. P. Andrade, R. P. Espíndola, N. Ebecken","doi":"10.4236/JILSA.2014.62009","DOIUrl":"https://doi.org/10.4236/JILSA.2014.62009","url":null,"abstract":"The coastal marine habitats \u0000are often characterized by high biological activity. Therefore, monitoring \u0000programs and conservation plans of coastal environments are needed. So, in \u0000order to contribute to decision making process of the Brazilian Information \u0000System of Coastal Management, this paper presents a preliminary analysis of the \u0000effects of simulated deletions of individual organisms within a planktonic \u0000network as knowledge acquisition platform. An in situ scanning flow cytometer was used to data acquisition. A \u0000static and undirected food web is generated and represented by a fuzzy graph \u0000structure. Our results show through a series of indices the main changes of \u0000these networks. It was also verified similar traits and properties with other \u0000food webs found in the literature.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-02DOI: 10.4236/JILSA.2014.62008
A. H. Al-Fatlawi, S. Ling, H. Lam
Technological advances and the enormous flood of papers have motivated many researchers and companies to innovate new technologies. In particular, handwriting recognition is a very useful technology to support applications like electronic books (eBooks), post code readers (that sort mails in post offices), and some bank applications. This paper proposes three systems to discriminate handwritten graffiti digits (0 to 9) and some commands with different architectures and abilities. It introduces three classifiers, namely single neural network (SNN) classifier, parallel neural networks (PNN) classifier and tree-structured neural network (TSNN) classifier. The three classifiers have been designed through adopting feed forward neural networks. In order to optimize the network parameters (connection weights), the back-propagation algorithm has been used. Several architectures are applied and examined to present a comparative study about these three systems from different perspectives. The research focuses on examining their accuracy, flexibility and scalability. The paper presents an analytical study about the impacts of three factors on the accuracy of the systems and behavior of the neural networks in terms of the number of the hidden neurons, the model of the activation functions and the learning rate. Therefore, future directions have been considered significantly in this paper through designing particularly flexible systems that allow adding many more classes in the future without retraining the current neural networks.
{"title":"A Comparison of Neural Classifiers for Graffiti Recognition","authors":"A. H. Al-Fatlawi, S. Ling, H. Lam","doi":"10.4236/JILSA.2014.62008","DOIUrl":"https://doi.org/10.4236/JILSA.2014.62008","url":null,"abstract":"Technological \u0000advances and the enormous flood of papers have motivated many researchers and \u0000companies to innovate new technologies. In particular, handwriting recognition \u0000is a very useful technology to support applications like electronic books \u0000(eBooks), post code readers (that sort mails in post offices), and some bank \u0000applications. This paper proposes three systems to discriminate handwritten \u0000graffiti digits (0 to 9) and some commands with different architectures and \u0000abilities. It introduces three classifiers, namely single neural network (SNN) \u0000classifier, parallel neural networks (PNN) classifier and tree-structured \u0000neural network (TSNN) classifier. The three classifiers have been designed \u0000through adopting feed forward neural networks. In order to optimize the network \u0000parameters (connection weights), the back-propagation algorithm has been used. \u0000Several architectures are applied and examined to present a comparative study \u0000about these three systems from different perspectives. The research focuses on \u0000examining their accuracy, flexibility and scalability. The paper presents an \u0000analytical study about the impacts of three factors on the accuracy of the \u0000systems and behavior of the neural networks in terms of the number of the \u0000hidden neurons, the model of the activation functions and the learning rate. \u0000Therefore, future directions have been considered significantly in this paper \u0000through designing particularly flexible systems that allow adding many more \u0000classes in the future without retraining the current neural networks.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-02DOI: 10.4236/JILSA.2014.62007
Hugo Araujo, Bo Xiao, Chuang Liu, Yanbin Zhao, H. Lam
This paper presents the automatic drug administration for the regulation of bispectral (BIS) index in the anesthesia process during the clinical surgery by controlling the concentration target of two drugs, namely, propofol and remifentanil. To realize the automatic drug administration, real clinical data are collected for 42 patients for the construction of patients’ models consisting of pharmacokinetic and pharmacodynamic models describing the dynamics reacting to the input drugs. A nominal anesthesia model is obtained by taking the average of 42 patients’ models for the design of control scheme. Three PID controllers are employed, namely linear PID controller, type-1 (T1) fuzzy PID controller and interval type-2 (IT2) fuzzy PID controller, to regulate the BIS index using the nominal patient’s model. The PID gains and membership functions are obtained using genetic algorithm (GA) by minimizing a cost function measuring the control performance. The best trained PID controllers are tested under different scenarios and compared in terms of control performance. Simulation results show that the IT2 fuzzy PID controller offers the best control strategy regulating the BIS index while the T1 fuzzy PID controller comes the second.
{"title":"Design of Type-1 and Interval Type-2 Fuzzy PID Control for Anesthesia Using Genetic Algorithms","authors":"Hugo Araujo, Bo Xiao, Chuang Liu, Yanbin Zhao, H. Lam","doi":"10.4236/JILSA.2014.62007","DOIUrl":"https://doi.org/10.4236/JILSA.2014.62007","url":null,"abstract":"This paper presents the automatic drug administration for the regulation of bispectral (BIS) index in the anesthesia process during the clinical surgery by controlling the concentration target of two drugs, namely, propofol and remifentanil. To realize the automatic drug administration, real clinical data are collected for 42 patients for the construction of patients’ models consisting of pharmacokinetic and pharmacodynamic models describing the dynamics reacting to the input drugs. A nominal anesthesia model is obtained by taking the average of 42 patients’ models for the design of control scheme. Three PID controllers are employed, namely linear PID controller, type-1 (T1) fuzzy PID controller and interval type-2 (IT2) fuzzy PID controller, to regulate the BIS index using the nominal patient’s model. The PID gains and membership functions are obtained using genetic algorithm (GA) by minimizing a cost function measuring the control performance. The best trained PID controllers are tested under different scenarios and compared in terms of control performance. Simulation results show that the IT2 fuzzy PID controller offers the best control strategy regulating the BIS index while the T1 fuzzy PID controller comes the second.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-02DOI: 10.4236/JILSA.2014.62006
Adel Elgammal
This paper presents a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) driven Self-Excited Induction Generator (SEIG). The aim of the developed control method is to automatically tune and optimize the scaling factors and the membership functions of the Fuzzy Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated voltage source PWM converters with a carrier-based Sinusoidal PWM modulation for both Generator- and Grid-side converters have been connected back to back between the generator terminals and utility grid via common DC link. The indirect vector control scheme is implemented to maintain balance between generated power and power supplied to the grid and maintain the terminal voltage of the generator and the DC bus voltage constant for variable rotor speed and load. Simulation study has been carried out using the MATLAB/Simulink environment to verify the robustness of the power electronics converters and the effectiveness of proposed control method under steady state and transient conditions and also machine parameters mismatches. The proposed control scheme has improved the voltage regulation and the transient performance of the wave energy scheme over a wide range of operating conditions.
{"title":"Adaptive Fuzzy Sliding Mode Controller for Grid Interface Ocean Wave Energy Conversion","authors":"Adel Elgammal","doi":"10.4236/JILSA.2014.62006","DOIUrl":"https://doi.org/10.4236/JILSA.2014.62006","url":null,"abstract":"This paper presents \u0000a closed-loop vector control structure based on adaptive Fuzzy Logic Sliding \u0000Mode Controller (FL-SMC) for a grid-connected Wave Energy Conversion System (WECS) \u0000driven Self-Excited Induction Generator (SEIG). The aim of the developed \u0000control method is to automatically \u0000tune and optimize the scaling factors and the membership functions of the Fuzzy \u0000Logic Controllers (FLC) using Multi-Objective Genetic Algorithms (MOGA) and \u0000Multi-Objective Particle Swarm Optimization (MOPSO). Two Pulse Width Modulated \u0000voltage source PWM converters with a carrier-based Sinusoidal PWM modulation \u0000for both Generator- and Grid-side converters have been connected back to back between \u0000the generator terminals and utility grid via common DC link. The indirect vector control scheme is \u0000implemented to maintain balance between generated power and power supplied to \u0000the grid and maintain the terminal \u0000voltage of the generator and the DC bus voltage constant for variable rotor \u0000speed and load. Simulation study has \u0000been carried out using the MATLAB/Simulink environment to verify the \u0000robustness of the power electronics converters and the effectiveness of \u0000proposed control method under steady state and transient conditions and also \u0000machine parameters mismatches. The \u0000proposed control scheme has improved the voltage regulation and the \u0000transient performance of the wave energy scheme over a wide range of operating \u0000conditions.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-01-27DOI: 10.4236/JILSA.2014.61005
Md. Al Mehedi Hasan, M. Nasser, B. Pal, Shamim Ahmad
The success of any Intrusion Detection System (IDS) is a complicated problem due to its nonlinearity and the quantitative or qualitative network traffic data stream with many features. To get rid of this problem, several types of intrusion detection methods have been proposed and shown different levels of accuracy. This is why the choice of the effective and robust method for IDS is very important topic in information security. In this work, we have built two models for the classification purpose. One is based on Support Vector Machines (SVM) and the other is Random Forests (RF). Experimental results show that either classifier is effective. SVM is slightly more accurate, but more expensive in terms of time. RF produces similar accuracy in a much faster manner if given modeling parameters. These classifiers can contribute to an IDS system as one source of analysis and increase its accuracy. In this paper, KDD’99 Dataset is used and find out which one is the best intrusion detector for this dataset. Statistical analysis on KDD’99 dataset found important issues which highly affect the performance of evaluated systems and results in a very poor evaluation of anomaly detection approaches. The most important deficiency in the KDD’99 dataset is the huge number of redundant records. To solve these issues, we have developed a new dataset, KDD99Train+ and KDD99Test+, which does not include any redundant records in the train set as well as in the test set, so the classifiers will not be biased towards more frequent records. The numbers of records in the train and test sets are now reasonable, which make it affordable to run the experiments on the complete set without the need to randomly select a small portion. The findings of this paper will be very useful to use SVM and RF in a more meaningful way in order to maximize the performance rate and minimize the false negative rate.
{"title":"Support Vector Machine and Random Forest Modeling for Intrusion Detection System (IDS)","authors":"Md. Al Mehedi Hasan, M. Nasser, B. Pal, Shamim Ahmad","doi":"10.4236/JILSA.2014.61005","DOIUrl":"https://doi.org/10.4236/JILSA.2014.61005","url":null,"abstract":"The success of \u0000any Intrusion Detection System (IDS) is a complicated problem due to its \u0000nonlinearity and the quantitative or qualitative network traffic data stream \u0000with many features. To get rid of this problem, several types of intrusion \u0000detection methods have been proposed and shown different levels of accuracy. \u0000This is why the choice of the effective and robust method for IDS is very \u0000important topic in information security. In this work, we have built two models \u0000for the classification purpose. One is based on Support Vector Machines (SVM) \u0000and the other is Random Forests (RF). Experimental results show that either \u0000classifier is effective. SVM is slightly more accurate, but more expensive in \u0000terms of time. RF produces similar accuracy in a much faster manner if given \u0000modeling parameters. These classifiers can contribute to an IDS system as one \u0000source of analysis and increase its accuracy. In this paper, KDD’99 Dataset is used and find out which \u0000one is the best intrusion \u0000detector for this dataset. Statistical \u0000analysis on KDD’99 dataset found important issues which highly affect the \u0000performance of evaluated systems and results in a very poor evaluation of \u0000anomaly detection approaches. The most important deficiency in the KDD’99 dataset \u0000is the huge number of redundant records. To solve these \u0000issues, we have developed a new dataset, KDD99Train+ and KDD99Test+, which does \u0000not include any redundant records in the train set as well as in the test set, \u0000so the classifiers will not be biased towards more frequent records. The \u0000numbers of records in the train and test sets are now reasonable, which make it \u0000affordable to run the experiments on the complete set without the need to \u0000randomly select a small portion. The findings of this paper will be very useful \u0000to use SVM and RF in a more \u0000meaningful way in order to maximize the performance rate and minimize the false \u0000negative rate.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-01-27DOI: 10.4236/JILSA.2014.61001
Mohammad Yahya H. Al-Shamri, N. Al-Ashwal
Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.
{"title":"Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems","authors":"Mohammad Yahya H. Al-Shamri, N. Al-Ashwal","doi":"10.4236/JILSA.2014.61001","DOIUrl":"https://doi.org/10.4236/JILSA.2014.61001","url":null,"abstract":"Memory-based collaborative \u0000recommender system (CRS) computes the similarity between users based on their \u0000declared ratings. However, not all ratings are of the same importance to the \u0000user. The set of ratings each user weights highly differs from user to user \u0000according to his mood and taste. This is usually reflected in the user’s rating \u0000scale. Accordingly, many efforts have been done to introduce weights to the \u0000similarity measures of CRSs. This paper proposes fuzzy weightings for the most \u0000common similarity measures for memory-based CRSs. Fuzzy weighting can be \u0000considered as a learning mechanism for capturing the preferences of users for \u0000ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, \u0000effective and does not require any more space. Moreover, fuzzy weightings based \u0000on the rating deviations from the user’s mean of ratings take into account the \u0000different rating scales of different users. The experimental results \u0000show that fuzzy weightings obviously improve the CRSs performance to a good \u0000extent.","PeriodicalId":69452,"journal":{"name":"智能学习系统与应用(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4236/JILSA.2014.61001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70330005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-01-27DOI: 10.4236/JILSA.2014.61003
Asif Rahman, Siril Yella, M. Dougherty
Increasing costs and competitive business strategies are pushing sawmill enterprises to make an effort for optimization of their process management. Organizational decisions mainly concentrate on performance and reduction of operational costs in order to maintain profit margins. Although many efforts have been made, effective utilization of resources, optimal planning and maximum productivity in sawmill are still challenging to sawmill industries. Many researchers proposed the simulation models in combination with optimization techniques to address problems of integrated logistics optimization. The combination of simulation and optimization technique identifies the optimal strategy by simulating all complex behaviours of the system under consideration including objectives and constraints. During the past decade, an enormous number of studies were conducted to simulate operational inefficiencies in order to find optimal solutions. This paper gives a review on recent developments and challenges associated with simulation and optimization techniques. It was believed that the review would provide a perfect ground to the authors in pursuing further work in optimizing sawmill yard operations.
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