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Papers by Meysam Alizadeh
Advancing Technologies, 2012
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society, 2009
Contributions to Management Science, 2009
... Meysam Alizadeh ... one unit of demand to customer zone i from warehouse at site j, Cjk cost ... more ... Meysam Alizadeh ... one unit of demand to customer zone i from warehouse at site j, Cjk cost of supplying one unit of demand to warehouse at site j from plant at site k, F r j : fixed cost per unit of time for opening and operating warehouse with capacity level r at site j, Gh k : fixed ...
International Journal of Industrial Engineering Computations, 2011
... Design and analysis of experiments in ANFIS modeling for stock price prediction Meysam Alizad... more ... Design and analysis of experiments in ANFIS modeling for stock price prediction Meysam Alizadeha*, Mohsen Gharakhanib, Elnaz Fotoohic and Roy Radad ... Mascioli et al. (1997) proposed merging of min-max and ANFIS models to determine the optimal set of fuzzy rules. ...
International Journal of Intelligent Systems, 2011
Chapter 20 Facility Location in Supply Chain Meysam Alizadeh A supply chain (SC) is the network o... more Chapter 20 Facility Location in Supply Chain Meysam Alizadeh A supply chain (SC) is the network of facilities and activities that performs the function of product development, procurementof material from vendors, the move-ment of materials between facilities, the manufacturing of ...
Empirical evidences have supported the large heterogeneity in the timing of individuals' activiti... more Empirical evidences have supported the large heterogeneity in the timing of individuals' activities. Moreover, computational analysis of the agent-based models has shown the importance of the activation regimes. In this paper, we apply four different asynchronous updating schemes including random, uniform, and two state-driven Poisson updating schemes on an agent-based opinion dynamics model. We compare the effect of these activation regimes by measuring the appropriate opinion clustering statistics and also the number of emergent extremists. The results exhibit both qualitative and quantitative difference between different activation regimes which in some cases are counterintuitive. In particular, we find that exposing the radical/moderate agents to more encounters decreases/increases the average number of extremists compared to other types of activation regimes. The results also show that no specific updating scheme can always outperform the others in reaching to consensus.
We apply an agent-based opinion dynamics model to investigate the distribution of opinions and th... more We apply an agent-based opinion dynamics model to investigate the distribution of opinions and the size of opinion clusters. We use parameter sweeps to examine the sensitivity of opinion distributions and cluster sizes relative to changes in individuals' tolerance and uncertainty. Our results demonstrate that opinion distributions and cluster sizes are structurally unstable, not stationary, and have fat tails in most configurations of the model, rather than stable Gaussian distributions. Hence, extremist radical individuals occur far more frequently than " normally " expected. Opinion clusters, in addition to being fat-tailed, reveal a dynamic transition from lognormal to exponential distributions as parameters change.
Empirical findings from social psychology show that sometimes people show favoritism toward in-gr... more Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. [Adv. Complex Syst. 13(3) (2010) 405– 423], and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction.
Empirical findings in the intergroup conflict literature show that individuals' beliefs that mark... more Empirical findings in the intergroup conflict literature show that individuals' beliefs that mark differentiation from out-groups become radicalized as intergroup tensions escalate. They also show that this differentiation is proportional to tension escalation. In this paper, we are interested to develop an agent-based model which captures these findings in order to explore the effect of perceived intergroup conflict escalation on the average number of emergent extremists and opinion clusters in the population. The proposed model builds on the 2-dimensional bounded confidence model proposed by Huet et al (2008). The results show that the average number of extremists has a negative correlation with intolerance threshold and positive correlation with the amount of opinion movement when two agents are to reject each other's belief. In other words, the more tensions exist between groups, the more individuals getting extremists. We also found that intergroup conflict escalation leads to lower opinion diversity in the population compared with normal situations.
— Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling... more — Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling. However, since it includes many parameters needed to be set, its designing process is a complicated and time-intensive task for experimenters. To tackle this problem, in this paper we implement the Design of Experiment (DOE) technique to identify the significant parameters of ANFIS when it applies to the problem of stock price prediction. Using full factorial design, nine factors are considered as independent variables. Results identify six factors as statistically significant parameters, as well as four significant interactions between some independent variables.
Data driven neuro-fuzzy systems modeling requires the application of a suitable input selection m... more Data driven neuro-fuzzy systems modeling requires the application of a suitable input selection method to identify the most relevant input variables. In view of the substantial number of existing input selection algorithms applied in neuro-fuzzy modeling, the need arises to count on criteria that enable to adequately decide which algorithm to use in certain situations. In this paper, we analyze the performance of five fundamental and widely used input selection algorithms, which encompass both model-free methods and model-based methods. Each of these algorithms is discussed in detail, and thus, present a comprehensive comparative analysis. Finally, we compare the performances of these algorithms by applying in stock price prediction problem. The experiments and the results provide a precious insight about the advantages and drawbacks of these five input selection algorithms.
Journal Articles by Meysam Alizadeh
In this paper, we propose a class of models for generating spatial versions of three classic netw... more In this paper, we propose a class of models for generating spatial versions of three classic networks: Erdös-Rényi (ER), Watts-Strogatz (WS), and Barabási-Albert (BA). We assume that nodes have geographical coordinates, are uniformly distributed over an m 9 m Cartesian space, and long-distance connections are penalized. Our computational results show higher clustering coefficient, assorta-tivity, and transitivity in all three spatial networks, and imperfect power law degree distribution in the BA network. Furthermore, we analyze a special case with geographically clustered coordinates, resembling real human communities, in which points are clustered over k centers. Comparison between the uniformly and geographically clustered versions of the proposed spatial networks show an increase in values of the clustering coefficient, assortativity, and transitivity, and a lognormal degree distribution for spatially clustered ER, taller degree distribution and higher average path length for spatially clustered WS, and higher clustering coefficient and transitivity for the spatially clustered BA networks.
Advancing Technologies, 2012
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society, 2009
Contributions to Management Science, 2009
... Meysam Alizadeh ... one unit of demand to customer zone i from warehouse at site j, Cjk cost ... more ... Meysam Alizadeh ... one unit of demand to customer zone i from warehouse at site j, Cjk cost of supplying one unit of demand to warehouse at site j from plant at site k, F r j : fixed cost per unit of time for opening and operating warehouse with capacity level r at site j, Gh k : fixed ...
International Journal of Industrial Engineering Computations, 2011
... Design and analysis of experiments in ANFIS modeling for stock price prediction Meysam Alizad... more ... Design and analysis of experiments in ANFIS modeling for stock price prediction Meysam Alizadeha*, Mohsen Gharakhanib, Elnaz Fotoohic and Roy Radad ... Mascioli et al. (1997) proposed merging of min-max and ANFIS models to determine the optimal set of fuzzy rules. ...
International Journal of Intelligent Systems, 2011
Chapter 20 Facility Location in Supply Chain Meysam Alizadeh A supply chain (SC) is the network o... more Chapter 20 Facility Location in Supply Chain Meysam Alizadeh A supply chain (SC) is the network of facilities and activities that performs the function of product development, procurementof material from vendors, the move-ment of materials between facilities, the manufacturing of ...
Empirical evidences have supported the large heterogeneity in the timing of individuals' activiti... more Empirical evidences have supported the large heterogeneity in the timing of individuals' activities. Moreover, computational analysis of the agent-based models has shown the importance of the activation regimes. In this paper, we apply four different asynchronous updating schemes including random, uniform, and two state-driven Poisson updating schemes on an agent-based opinion dynamics model. We compare the effect of these activation regimes by measuring the appropriate opinion clustering statistics and also the number of emergent extremists. The results exhibit both qualitative and quantitative difference between different activation regimes which in some cases are counterintuitive. In particular, we find that exposing the radical/moderate agents to more encounters decreases/increases the average number of extremists compared to other types of activation regimes. The results also show that no specific updating scheme can always outperform the others in reaching to consensus.
We apply an agent-based opinion dynamics model to investigate the distribution of opinions and th... more We apply an agent-based opinion dynamics model to investigate the distribution of opinions and the size of opinion clusters. We use parameter sweeps to examine the sensitivity of opinion distributions and cluster sizes relative to changes in individuals' tolerance and uncertainty. Our results demonstrate that opinion distributions and cluster sizes are structurally unstable, not stationary, and have fat tails in most configurations of the model, rather than stable Gaussian distributions. Hence, extremist radical individuals occur far more frequently than " normally " expected. Opinion clusters, in addition to being fat-tailed, reveal a dynamic transition from lognormal to exponential distributions as parameters change.
Empirical findings from social psychology show that sometimes people show favoritism toward in-gr... more Empirical findings from social psychology show that sometimes people show favoritism toward in-group members in order to reach a global consensus, even against individuals' own preferences (e.g., altruistically or deontically). Here we integrate ideas and findings on in-group favoritism, opinion dynamics, and radicalization using an agent-based model entitled cooperative bounded confidence (CBC). We investigate the interplay of homophily, rejection, and in-group cooperation drivers on the formation of opinion clusters and the emergence of extremist, radical opinions. Our model is the first to explicitly explore the effect of in-group favoritism on the macro-level, collective behavior of opinions. We compare our model against the two-dimentional bounded confidence model with rejection mechanism, proposed by Huet et al. [Adv. Complex Syst. 13(3) (2010) 405– 423], and find that the number of opinion clusters and extremists is reduced in our model. Moreover, results show that group influence can never dominate homophilous and rejecting encounters in the process of opinion cluster formation. We conclude by discussing implications of our model for research on collective behavior of opinions emerging from individuals' interaction.
Empirical findings in the intergroup conflict literature show that individuals' beliefs that mark... more Empirical findings in the intergroup conflict literature show that individuals' beliefs that mark differentiation from out-groups become radicalized as intergroup tensions escalate. They also show that this differentiation is proportional to tension escalation. In this paper, we are interested to develop an agent-based model which captures these findings in order to explore the effect of perceived intergroup conflict escalation on the average number of emergent extremists and opinion clusters in the population. The proposed model builds on the 2-dimensional bounded confidence model proposed by Huet et al (2008). The results show that the average number of extremists has a negative correlation with intolerance threshold and positive correlation with the amount of opinion movement when two agents are to reject each other's belief. In other words, the more tensions exist between groups, the more individuals getting extremists. We also found that intergroup conflict escalation leads to lower opinion diversity in the population compared with normal situations.
— Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling... more — Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling. However, since it includes many parameters needed to be set, its designing process is a complicated and time-intensive task for experimenters. To tackle this problem, in this paper we implement the Design of Experiment (DOE) technique to identify the significant parameters of ANFIS when it applies to the problem of stock price prediction. Using full factorial design, nine factors are considered as independent variables. Results identify six factors as statistically significant parameters, as well as four significant interactions between some independent variables.
Data driven neuro-fuzzy systems modeling requires the application of a suitable input selection m... more Data driven neuro-fuzzy systems modeling requires the application of a suitable input selection method to identify the most relevant input variables. In view of the substantial number of existing input selection algorithms applied in neuro-fuzzy modeling, the need arises to count on criteria that enable to adequately decide which algorithm to use in certain situations. In this paper, we analyze the performance of five fundamental and widely used input selection algorithms, which encompass both model-free methods and model-based methods. Each of these algorithms is discussed in detail, and thus, present a comprehensive comparative analysis. Finally, we compare the performances of these algorithms by applying in stock price prediction problem. The experiments and the results provide a precious insight about the advantages and drawbacks of these five input selection algorithms.
In this paper, we propose a class of models for generating spatial versions of three classic netw... more In this paper, we propose a class of models for generating spatial versions of three classic networks: Erdös-Rényi (ER), Watts-Strogatz (WS), and Barabási-Albert (BA). We assume that nodes have geographical coordinates, are uniformly distributed over an m 9 m Cartesian space, and long-distance connections are penalized. Our computational results show higher clustering coefficient, assorta-tivity, and transitivity in all three spatial networks, and imperfect power law degree distribution in the BA network. Furthermore, we analyze a special case with geographically clustered coordinates, resembling real human communities, in which points are clustered over k centers. Comparison between the uniformly and geographically clustered versions of the proposed spatial networks show an increase in values of the clustering coefficient, assortativity, and transitivity, and a lognormal degree distribution for spatially clustered ER, taller degree distribution and higher average path length for spatially clustered WS, and higher clustering coefficient and transitivity for the spatially clustered BA networks.