Note: Intro -- Preface -- Organization -- Contents - Part I -- Contents -- Part II -- DNA Computing -- DNA Self-assembly Model to Solve Compound Logic Operators Problem -- 1 Introduction -- 2 The Principle of DNA Self-assembly -- 3 Compound Logic Operators -- 4 Theoretical Model of Compound Logic Operators -- 4.1 Initial Tile -- 4.2 Process Tile -- 4.3 Operation Tile -- 4.4 End Tile -- 4.5 Boundary Tile -- 5 The Model Instance of Compound Logic Operators -- 6 Conclusions -- References -- Model Checking Computational Tree Logic Using Sticker Automata -- 1 Introduction -- 2 Preliminary -- 2.1 The Basic Constructs in CTL 1 -- 2.2 Finite State Automata and Model Checking -- 2.3 Sticker Automata and DNA Model Checking -- 3 The DNA Model Checking Method for the Basic CTL Constructs -- 3.1 The DNA Model Checking for the Four Universal Formulas -- 3.2 The DNA Model Checking for the Four Existence Formulas -- 3.3 The DNA Model Checking for the Basic CTL Constructs -- 4 Simulated Experiments -- 5 Conclusions -- References -- Two-Digit Full Subtractor Logical Operation Based on DNA Strand Displacement -- 1 Introduction -- 2 DSD and Seesaw Motif of Basic Gates -- 3 Binary Two-Digit Subtractor and Dual-Rail Circuit -- 4 Seesaw Circuit and Simulation in Visual DSD -- 5 Conclusion -- References -- One-Bit Full Adder-Full Subtractor Logical Operation Based on DNA Strand Displacement -- 1 Introduction -- 2 The Background of DNA Strand Displacement -- 3 The Digit Circuit and Dual-rail Circuit -- 4 Seesaw Circuit and Simulation with Visual DSD -- 5 Conclusion -- References -- Logic Gate Based on Circular DNA Structure with Strand Displacement -- 1 Introduction -- 2 Design and Construction of Logic Gate Model -- 2.1 Principle of the Proposed Method: XOR Gate -- 2.2 Principle of the Proposed Method: AND Gate -- 3 Result and Discussion -- 4 Conclusions -- References. , The Working Operation Problem Based on Probe Machine Model -- 1 Introduction -- 2 The Probe Computing Principles -- 3 The Working Operation Problem Description -- 4 Conclusion -- References -- Matrix Flat Splicing Systems -- 1 Introduction -- 2 Preliminaries -- 3 Matrix Flat Splicing System -- 4 Application to Chain-Code Pictures -- 5 Conclusions and Discussions -- References -- A Universal Platform for Building DNA Logic Circuits -- 1 Introduction -- 2 Design and Construction of Half-adder and Half-subtract Model -- 2.1 Materials and Analysis -- 2.2 Design of Half-adder -- 2.3 Design of Half-subtract -- 3 Result and Discussion -- 4 Conclusions -- References -- Membrane Computing -- A Hybrid ``Fast-Slow'' Convergent Framework for Genetic Algorithm Inspired by Membrane Computing -- 1 Introduction -- 2 Related Technologies -- 2.1 Genetic Algorithm -- 2.2 Membrane Computing Inspired Algorithm -- 3 The Model and Data Experiments -- 3.1 GA Program -- 3.2 Membrane Structure -- 3.3 Data Experiments -- 4 Conclusion -- References -- An Image Threshold Segmentation Algorithm with Hybrid Evolutionary Mechanisms Based on Membrane Computing -- 1 Introduction -- 2 Principle of Threshold Images Segmentation -- 3 Threshold Segmentation Membrane Algorithm -- 3.1 Object of the Tissue-Link Membrane System -- 3.2 Hybrid Evolutionary Rule and Communication Rules -- 4 Experiment Analysis -- 4.1 Data Sets Used in the Experiments -- 4.2 Parameter Configuration in Experiments -- 4.3 Algorithm Analysis and Comparison -- 5 Conclusion -- References -- K-Medoids-Based Consensus Clustering Based on Cell-Like P Systems with Promoters and Inhibitors -- 1 Introduction -- 2 Preliminaries -- 2.1 The K-Medoids Algorithm -- 2.2 The Consensus Clustering -- 2.3 Cell-like P System with Promoters and Inhibitors. , 3 The K-Medoids-Based Consensus Clustering Based on Cell-like P Systems with Promoters and Inhibitors -- 3.1 The Cell-like P System for CPPI-KMCC -- 3.2 Time Complexity Analysis -- 4 Experiments and Analysis -- 5 Conclusions -- References -- Fault Classification of Power Transmission Lines Using Fuzzy Reasoning Spiking Neural P Systems -- 1 Introduction -- 2 Fault Classification with FRSNPS -- 2.1 Fuzzy Production Rules of Fault Classification -- 2.2 Fault Classification Models -- 3 Experiments -- 4 Conclusions -- References -- Membrane Algorithm with Genetic Operation and VRPTW-Based Public Optimization System -- 1 Introduction -- 2 Definition and Mathematical Mode for VRPTW -- 2.1 Definition for VRPTW -- 2.2 Mathematical Model for VRPTW -- 3 Membrane Algorithm with GA Evolution Machanism -- 3.1 Membrane Configuration of MGA -- 3.2 Coding for Objects -- 3.3 The Rules in Membranes -- 3.4 Transportation Mechanism of MGA -- 3.5 Termination Condition and Output -- 4 Application of MGA in VRPTW -- 5 Simulation Experiment -- 5.1 Results for Parameters Tuning -- 5.2 Analysis of Experiment Results for Different Scales -- 6 Conclusion -- References -- An Immune Algorithm Based on P System for Classification -- 1 Introduction -- 2 Related Works -- 2.1 Cell-Like P System -- 2.2 Negative Selection -- 3 NS for Classification -- 3.1 Definition -- 3.2 Rule Set -- 3.3 Algorithm Implementation -- 3.4 Analyses -- 4 Conclusion -- References -- Simulation of Fuzzy ACSH on Membranes with Michaelis-Menten Kinetics -- 1 Introduction -- 2 Preliminaries -- 2.1 Kinetic Studies of the Sulfoxidation Reactions -- 2.2 P System with Proteins on Membranes -- 2.3 Fuzzy Artificial Cell System with Proteins on Membranes -- 3 Simulation of FACSP -- 3.1 FACSP in Oxidation of Sulfides -- 3.2 Behaviour of FACSP -- 3.3 Mathematical Modeling and Simulation of FACSP -- 4 Conclusion. , References -- A Family P System of Realizing RSA Algorithm -- 1 Introduction -- 2 RSA Algorithm -- 3 Design of the P System -- 3.1 The Definition of the RSA P System -- 3.2 Key Generation Membrane A2 -- 3.3 Encryption and Decryption Membrane A3 -- 3.4 Skin Membrane A1 -- 4 Instance -- 4.1 Key Generation -- 4.2 Encryption and Decryption -- 5 Conclusions -- References -- A General Object-Oriented Description for Membrane Computing -- 1 Introduction -- 2 Preliminaries -- 3 The Object-Oriented Description of Membrane Computing -- 4 The Data Structure of Membrane Computing -- 5 An Object-Oriented Static Model of Membrane Computing -- 6 Object-Oriented Dynamic Model of Membrane Computing -- 6.1 The Activity Diagram -- 6.2 The Sequence Diagrams -- 6.3 The Use-Case Diagram -- 7 Conclusion and Discussion -- References -- Matrix Representation of Parallel Computation for Spiking Neural P Systems -- 1 Introduction -- 2 SN P Systems -- 3 Matrix Representation of SN P Systems with Delay -- 4 Two Illustration Examples -- 5 Conclusions and Future Work -- References -- The Computational Power of Array P System with Mate Operation -- 1 Introduction -- 2 Preliminaries -- 2.1 Array P System [10] -- 2.2 Mate Operation [3] -- 3 Array P System with Mate Operation -- 3.1 Definition -- 3.2 Example -- 3.3 Theorem -- 4 Closure Properties -- 4.1 Theorem -- 4.2 Theorem -- 5 Generative Power -- 5.1 Theorem -- 5.2 Theorem -- 5.3 Theorem -- 5.4 Definition -- 5.5 Theorem -- 6 Conclusion -- References -- The Computational Power of Watson-Crick Grammars: Revisited -- 1 Introduction -- 2 Preliminaries -- 3 The Computational Power -- 4 Conclusions -- References -- An Improvement of Small Universal Spiking Neural P Systems with Anti-Spikes -- 1 Introduction -- 2 Prerequisites -- 2.1 Universal Register Machine -- 2.2 Spiking Neural P Systems with Anti-Spikes. , 3 A Small Universal SN P System with Anti-Spike -- 3.1 The Structure of Neuron state -- 3.2 The Structure of Auxiliary Neurons a -- 4 Proof and Conclusion -- 4.1 Module ADD (Simulating li:(ADD(r),lj,lk)) -- 4.2 Module SUB (Simulating li:(SUB(r),lj,lk)) -- 4.3 Module OUTPUT -- 5 Conclusions and Remark -- References -- The Implementation of Membrane Clustering Algorithm Based on FPGA -- 1 Introduction -- 2 Membrane Clustering Algorithm -- 2.1 Structure of Membrane Clustering Algorithm -- 2.2 Object Representation in the Structure of the Membrane Clustering Algorithm -- 2.3 Learning Algorithm -- 3 Parallel Implementation of the Membrane Clustering Algorithm on FPGA -- 3.1 FPGA Parallel Computing Principle -- 3.2 Implementation Process of Membrane Clustering Algorithm on FPGA -- 3.3 Implementation Program Module Partitioning of Membrane Clustering Algorithm on FPGA -- 4 Experiment Results and Analysis -- 5 Conclusions -- References -- Tools and Simulators for Membrane Computing-A Literature Review -- 1 Introduction -- 2 Classification of Membrane Computing Tools -- 3 P System Tools that are Specific to a Particular Application or Type -- 3.1 Membrane Computing in Prolog -- 3.2 On a LISP Implementation of a Class of P Systems -- 3.3 Membrane Simulator -- 3.4 A CLIPS Simulator for Recognizer P Systems with Active Membranes -- 3.5 A MzScheme Implementation of Transition P Systems -- 3.6 Simulation of Transition P System Using Haskell -- 3.7 Distributed Simulator for Transition P System -- 3.8 SubLP-Studio -- 3.9 A Prolog Simulator for Deterministic P Systems with Active Membranes -- 3.10 Modelling Biological Processes by Using a Probabilistic P System Software -- 3.11 P Systems Running on a Cluster of Computers -- 3.12 SimCM -- 3.13 Conformon P System -- 3.14 Simulator for Confluent P Systems -- 3.15 Simulator for Dynamical Probabilistic P System. , 3.16 Tissue Simulator: Tissue Based P System.

Note: Intro -- Preface -- Organization -- Contents -- Evolutionary Computation and Swarm Intelligence -- Wingsuit Flying Search Enhanced by Spherical Evolution -- 1 Introduction -- 2 Wingsuit Flying Search -- 2.1 Generating Initial Points -- 2.2 Determining Neighborhood Size for Each Point -- 2.3 Generating Neighborhood Points -- 2.4 Generating Centroid and Random Point -- 3 Spherical Evolution -- 4 Wingsuit Flying Search Enhanced by Spherical Evolution -- 5 Experimental Results -- 6 Conclusion -- References -- Adaptive Total Variation Constraint Hypergraph Regularized NMF and Its Application on Single-Cell RNA-Seq Data -- 1 Introduction -- 2 Related Work -- 2.1 Adaptive Total Variation -- 2.2 Hypergraph Theory -- 3 Method -- 3.1 ATV-HNMF -- 3.2 Optimization -- 4 Experimental Results and Discussion -- 4.1 Datasets -- 4.2 Performance Evaluation and Comparisons -- 5 Conclusion -- References -- Covariance Matrix Adaptation Evolutionary Algorithm for Multi-task Optimization -- 1 Introduction -- 2 Background -- 2.1 Multifactorial Optimization -- 2.2 Covariance Matrix Adaptation Evolutionary Strategy -- 3 Covariance Matrix Adaptation Evolutionary Multitask Optimization -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Experimental Results and Discussion -- 5 Conclusions -- References -- Short Text Similarity Calculation Based on Jaccard and Semantic Mixture -- 1 Introduction -- 2 Related Algorithms -- 2.1 Jaccard Algorithm -- 2.2 Semantic Algorithm Based on Word Vector -- 2.3 Algorithm Based on Jaccard and Semantics -- 3 Experiment Design and Result Analysis -- 3.1 Experimental Details -- 3.2 Experimental Results and Analysis -- 4 Conclusion -- References -- Density-Based Population Initialization Strategy for Continuous Optimization -- 1 Introduction -- 2 Related Work -- 2.1 Population Initialization Strategies -- 2.2 Kernel Density Estimation. , 3 Proposed Algorithm -- 4 Experiments -- 4.1 Experiments on Uniformity Analysis -- 4.2 Experiments on CEC2013 Multimodal Optimization Benchmark -- 5 Conclusion -- References -- Intelligent Prediction and Optimization of Extraction Process Parameters for Paper-Making Reconstituted Tobacco -- 1 Introduction -- 2 Prediction Models of Extraction Process -- 2.1 Test Data and Processing -- 2.2 Artificial Neural Network Model of Extraction Process -- 2.3 Ensemble Learning Model of Extraction Process -- 2.4 Comparison of Two Prediction Models -- 3 Optimization of Process Parameters -- 4 Conclusion -- References -- Point Cloud Registration Using Evolutionary Algorithm -- 1 Introduction -- 2 Background -- 3 The Proposed EAs -- 3.1 The GA-Based Algorithm -- 3.2 The EDA-Based Algorithm -- 4 Experimental Study -- 5 Conclusion -- References -- Heterogeneous Distributed Flow Shop Scheduling and Reentrant Hybrid Flow Shop Scheduling in Seamless Steel Tube Manufacturing -- 1 Introduction -- 2 Problem Description -- 2.1 Description of RHFSP -- 2.2 Formulation of RHFSP -- 3 Algorithms for DFSP and RHFSP -- 3.1 The Discrete Fruit Fly Optimization Algorithm for DFSP -- 3.2 The Simulated Annealing Algorithm for RHFSP -- 4 Computational Results -- 5 Conclusion -- References -- Hyperchaotic Encryption Algorithm Based on Joseph Traversal and Bit Plane Reconstruction -- 1 Introduction -- 2 Basic Theory -- 2.1 Hyperchaotic Lorenz System -- 2.2 Joseph Problem -- 2.3 DNA Coding -- 3 Encryption Scheme -- 3.1 Key Generation -- 3.2 Pixel Position Scrambling -- 3.3 Bit Plane Reconstruction -- 3.4 Diffusion Algorithm -- 3.5 Encryption Step -- 3.6 Simulation Result -- 4 Performance Analysis -- 4.1 Key Space Analysis -- 4.2 Differential Attack Analysis -- 4.3 Key Sensitivity Analysis -- 4.4 Histogram Analysis -- 4.5 Correlation Analysis -- 4.6 Information Entropy Analysis. , 5 Conclusion -- References -- Trimmed Data-Driven Evolutionary Optimization Using Selective Surrogate Ensembles -- 1 Introduction -- 2 The Proposed TDDEA-SE Algorithm -- 2.1 The Framework -- 2.2 Trimmed Bagging -- 3 Experiments -- 3.1 Comparison of the Trim Ratio r -- 3.2 Comparison with Offline Data-Driven EAs -- 4 Conclusion -- References -- Research and Application of the Standard Formulation Technology for Three Kinds of Specialized Raw Materials -- 1 Introduction -- 2 Establishment and Optimization of the Standard Model of Three Kinds of Specialized Raw Materials -- 2.1 The Model of Specialized Raw Material for Three Kinds of Products Was Established -- 2.2 Optimize the Raw Material Model for Three Kinds of Products -- 3 Improvement of Quality Standard Method for Three Kinds of Specialized Raw Materials -- 3.1 The Residual Analysis Method Preprocesses the Data -- 3.2 Comparison and Analysis of Three Forecasting Methods of Product Index -- 4 Simulation Application of Three Kinds of Specialized Raw Material Model -- 4.1 The Standard Forecasting Model of Three Kinds of Specialized Raw Materials is Solved -- 4.2 The Standard Optimization Model of Three Kinds of Specialized Raw Materials Is Solved -- 4.3 The Final Results of the Indexes and Standards of the Three Specialized Raw Materials -- 5 Conclusion -- References -- A Hybrid Harmony Search Algorithm Based on Data Analysis to Solve Multi-objective Grain Transportation Problem -- 1 Introduction -- 2 Problem Definition -- 3 The Hybrid Harmony Search Algorithm Based on Data Analysis -- 3.1 Basic Elements of HSA-DA -- 3.2 Improvisation Process -- 3.3 Neighborhood Search Operators -- 3.4 The Data Analysis Method -- 3.5 Parameter Adjustment -- 4 Experimental Results and Comparisons -- 5 Conclusion -- References -- Chicken Swarm Optimization Algorithm Based on Hybrid Improvement Strategy. , 1 Introduction -- 2 Basic Chicken Swarm Optimization Algorithm -- 3 Chicken Swarm Optimization Algorithm Based on Hybrid Improvement Strategy -- 3.1 Chaotic Mapping Initialization Strategy -- 3.2 Cosine Inertia Weighting Strategy -- 3.3 Reverse Learning Strategy -- 3.4 Framework of HICSO -- 4 Experiment and Analysis -- 5 Conclusion -- References -- A Data-Driven Model Analysis Method in Optimizing Raw Materials Standard for Glutinous Rice Products -- 1 Introduction -- 2 Problem Description and Methods -- 2.1 Raw Material Standard Formulation Problem for the Glutinous Rice Product -- 2.2 Method for Solving the Raw Material Standard Formulation Problem for the Glutinous Rice Product -- 2.3 The Design Idea of Three-Stage Data-Driven Model Analysis Method -- 2.4 The Three-Stage Data-Driven Modeling Analysis Method -- 2.5 Experimental Data -- 2.6 Statistical Analysis -- 3 Results -- 3.1 Results of Each Step of the Prediction Stage -- 3.2 Results of Each Atep of Modeling Stage -- 3.3 Results of Each Step of Regulation Stage -- 4 Conclusions -- References -- Incorporating the Confusion Effect into the Simulated Evolution of Crowded Selfish Herds -- 1 Introduction -- 2 Model Design -- 2.1 Mathematical Formulation -- 2.2 Adopted Model Framework -- 2.3 Adjustments and Metrics -- 3 Results -- 3.1 Simulation Overview -- 3.2 The Emergent Schooling Patterns -- 3.3 The Emergent Wiggling Patterns -- 3.4 Robustness Analysis -- 4 Discussions -- References -- Multiobjective Brainstorm Optimization with Diversity Preservation Mechanism for Nonlinear Equation Systems -- 1 Introduction -- 2 Proposed Approach -- 2.1 Multilayer Bi-objective Transformation Technique -- 2.2 Multiobjective BSO Algorithm with Diversity Preservation Mechanism -- 3 Experimental Study and Discussions -- 3.1 Test Functions and Performance Criteria -- 3.2 Comparison with Other State-of-Art Methods. , 4 Conclusions -- References -- Solving Nonlinear Equations Systems with a Two-Phase Root-Finder Based on Niching Differential Evolution -- 1 Introduction -- 2 Proposed Algorithm -- 2.1 Global Search -- 2.2 Distribution Adjustment Local Search (DALS) -- 2.3 TPNDE -- 3 Experiments -- 3.1 Test Functions and Performance Metrics -- 3.2 Effects of TPNDE Components -- 3.3 Comparisons with Other Methods -- 4 Conclusion -- References -- Energy-Efficient Data Gathering Scheme Based on Compressive Sensing and Directional Walk Routing in Lossy WSNs -- 1 Introduction -- 2 Preliminaries -- 2.1 CS Background -- 2.2 Problem Formulation and Network Model -- 3 Proposed Solution -- 3.1 Constructing Sparse Random Matrix -- 4 Proposed CS-DWR Algorithm -- 5 Analysis of the Energy Balance -- 6 Performance Evaluation and Analysis -- 7 Conclusion -- References -- Neural Network and Machine Learning -- Predicting Locus-Specific DNA Methylation Based on Deep Neural Network -- 1 Introduction -- 2 Materials and Methods -- 2.1 Overall Framework -- 2.2 Dataset -- 2.3 Preprocessing -- 2.4 Feature Extraction with DNN -- 2.5 RF Classifier -- 2.6 Evaluation Methods -- 3 Experimental Results and Discussions -- 4 Conclusion -- References -- Pulse Recognition of Cardiovascular Disease Patients Based on One-Dimensional Convolutional Neural Network -- 1 Introduction -- 2 Pulse Data Collection and Processing -- 2.1 Pulse Data Collection -- 2.2 Data Preprocessing and Expansion -- 3 Neural Network Structure of Pulse Classification -- 3.1 The Difference Between 1D-CNN and 2D-CNN -- 3.2 Network Structure -- 4 The Results and Analysis of the Experiment -- 4.1 Prepare the Data Set -- 4.2 Analysis of Results -- 5 Conclusion -- References -- Machine Learning Meets Big Data: An Overview of Diagnostic and Prognostic Prediction for Cancer -- 1 Introduction -- 2 Omics Data -- 2.1 Genomics. , 2.2 Transcriptomics.

Note: Intro -- Preface -- Organization -- Contents -- Part II -- Contents - Part I -- Evolutionary Computing -- Kernel Evolutionary Algorithm for Clustering -- 1 Introduction -- 2 Existing Problems and Kernel Methods -- 3 Kernel Evolutionary Clustering Algorithm -- 3.1 Kernel Function Used in KECA -- 3.2 Evolutionary Strategies of KECA -- 4 Experimental Study -- 5 Concluding Remarks -- References -- A Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem -- 1 Introduction -- 2 Multi-objective Optimization -- 3 Related Work -- 4 Multi-parent Crossover Based Genetic Algorithm -- 4.1 Hypervolume Contribution Selection -- 4.2 Genetic Algorithm -- 5 Experiments -- 5.1 Parameters Settings -- 5.2 Performance Assessment Protocol -- 5.3 Computational Results -- 6 Conclusion -- References -- Unsupervised Image Segmentation Based on Watershed and Kernel Evolutionary Clustering Algorithm -- 1 Introduction -- 2 Watershed Algorithm -- 2.1 Principle and Characteristics of Watershed Algorithm -- 2.2 Mathematical Description of Watershed Algorithm -- 2.3 Marker Driven Watershed Transformation -- 3 Kernel Evolutionary Clustering Algorithm -- 3.1 Kernel Method -- 3.2 Kernel Evolutionary Clustering Algorithm -- 4 Algorithm of WKECA -- 5 Experiments -- 5.1 Results on the Nature Image -- 5.2 Results on the Texture Image -- 5.3 Results on the SAR Image -- 6 Conclusion -- References -- Classification Based on Fireworks Algorithm -- 1 Introduction -- 2 Fireworks Algorithm -- 3 Classification Method Based on EA -- 4 Experiments and Comparisons -- 4.1 Data Sets Used in Classification -- 4.2 Parameter Settings for FWA -- 4.3 Experimental Results and Analysis -- 5 Conclusion -- References -- Overlapping Community Detection in Network: A Fuzzy Evaluation Approach -- 1 Introduction -- 2 Relate Work -- 2.1 Fuzzy Evaluation. , 2.2 The Proposed Algorithm -- 3 Experiments -- 4 Conclusions -- References -- Multifactorial Brain Storm Optimization Algorithm -- 1 Introduction -- 2 Multifactorial Brain Storm Optimization Algorithm -- 3 Experiments -- 3.1 Test Problems -- 3.2 Definitions of Related Terms -- 3.3 Experiment 1: Problem-Sets with the Same Dimensionalities but Separated Optima -- 3.4 Experiment 2: Three Tasks of the Same Dimension and the Separated Optima -- 4 Conclusion -- References -- An Improved Heuristic Algorithm for UCAV Path Planning -- 1 Introduction -- 2 Related Works -- 2.1 Basic Mathematical Model -- 3 Path Planning Methods Based on Sparse A* Searching Algorithm -- 3.1 Extensible Rules of Nodes -- 3.2 Trajectory Cost Function -- 3.3 Trajectory Smooth Straighten Processing -- 4 Experimental Study -- 5 Conclusion -- References -- An Efficient Benchmark Generator for Dynamic Optimization Problems -- 1 Introduction -- 2 Free Peaks -- 2.1 One Peak Function -- 2.2 Partition the Search Space -- 2.3 Setup of the Sub-space -- 2.4 Time Complexity -- 3 Constructing Dynamic Optimization Problems -- 3.1 The Change in a Peak's Location Within the Peak's Basin -- 3.2 The Change in the Size of a Peak's Basin of Attraction -- 3.3 The Change in a Peak's Height -- 3.4 The Change in the Number of Peaks -- 4 Experimental Studies -- 4.1 Comparison of Computing Efficiency -- 4.2 The Performance of Existing Algorithms -- 5 Conclusions -- References -- Ensemble of Different Parameter Adaptation Techniques in Differential Evolution -- 1 Introduction -- 2 Our Approach: EADE -- 2.1 The Framework -- 2.2 EADE -- 3 Experimental Results and Analysis -- 3.1 Benchmark Functions -- 3.2 Parameter Settings -- 3.3 Compared with jDE and SHADE -- 4 Conclusions and Future Work -- References. , Research on Multimodal Optimization Algorithm for the Contamination Source Identification of City Water Distribution Networks -- 1 Introduction -- 2 Contamination Source Identification Problem Model -- 3 Solving Contamination Source Identification Problem Based on Niching Genetic Algorithm -- 4 Experimental Simulation and Analysis -- 4.1 Parameters Setting of Water Distribution Networks and Algorithm -- 4.2 Experiment: Result Analysis -- 5 Conclusion -- References -- Visual Tracking by Sequential Cellular Quantum-Behaved Particle Swarm Optimization Algorithm -- 1 Introduction -- 2 Related Work -- 2.1 Particle Filter -- 2.2 Cellular QPSO (cQPSO) Algorithm -- 3 Improved Sequential cQPSO Algorithm for Target Tracking -- 3.1 The Improvement on the Particle Initialization -- 3.2 The Improvement on the State Representation of Particles -- 3.3 The Improvement on MOG Appearance Mode -- 3.4 The Improvement on Resampling -- 3.5 The Improved Sequential RscQPSO Based Tracking Algorithm -- 4 Experimental Results -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusion -- References -- An Improved Search Algorithm About Spam Firewall -- 1 Introduction -- 2 Theoretical Foundation -- 2.1 Bilinear Diffe-Hellman Problem -- 2.2 Public Key Encryption with Keyword Search -- 3 Transformation Plan of Mail System -- 3.1 Generation of the Key -- 3.2 Mail Encryption of Sender -- 3.3 The Settings of the Mail Recipients' Trapdoor and Black and White Lists -- 3.4 Sorting and Filtering the Mail Servers -- 4 Security and Efficiency Analysis -- 4.1 Security Analysis -- 4.2 Efficiency Analysis -- 5 Conclusion -- References -- Artificial Bee Colony Algorithm Based on Clustering Method and Its Application for Optimal Power Flow Problem -- 1 Introduction -- 2 Optimal Power Flow Problem Formulation -- 2.1 Minimization of Total Fuel Cost -- 2.2 Minimization of Total Power Losses. , 2.3 Total Emission Cost Minimization -- 3 CMOABC Algorithm -- 4 Multi-objective Optimal Power Flow Based on CMOABC -- 5 Conclusions -- References -- Study on Hybrid Intelligent Algorithm with Solving Pre-stack AVO Elastic Parameter Inversion Problem -- 1 Introduction -- 2 Pre-stack AVO Elastic Parameter Inversion Problem -- 3 Pre-stack AVO Elastic Parameter Inversion Based on Intelligent Algorithm -- 3.1 Population Space and Initialization -- 3.2 Simulated Annealing Strategy -- 4 Experimental Simulation and Analysis -- 5 Conclusion -- References -- A Hybrid Multi-objective Discrete Particle Swarm Optimization Algorithm for Cooperative Air Combat DWTA -- 1 Introduction -- 2 The Cooperative Air Combat Model for DWTA -- 2.1 The DWTA Multi-objective Optimization Model -- 3 HMODPSO Algorithm for DWTA -- 3.1 Particle Encoding -- 3.2 The Leader Particle Selecting -- 3.3 Repairing Operator -- 3.4 Cauchy Mutation -- 3.5 Neighborhood Search -- 4 Simulations and Results -- 5 Conclusions -- References -- A Novel Image Fusion Method Based on Shearlet and Particle Swarm Optimization -- 1 Introduction -- 2 Shearlet -- 3 Particle Swarm Optimization -- 4 Multi-focus Image Fusion Algorithm Based on Shearlet and PSO -- 4.1 Introduction to Evaluation Criteria -- 4.2 Multi-focus Image Fusion Based on Shearlet and PSO -- 5 Experiments and Analysis -- 6 Conclusion -- References -- Generalized Project Gradient Algorithm for Solving Constrained Minimax Problems -- 1 Introduction -- 1.1 Description of Algorithm -- 2 Global Convergence of Algorithm -- 3 Numerical Experiments -- References -- A Real Adjacency Matrix-Coded Differential Evolution Algorithm for Traveling Salesman Problems -- 1 Introduction -- 2 Real Adjacency Matrix-Coding Mechanism -- 2.1 TSP Prototype -- 2.2 Coding Mechanism for TSP -- 3 A Real Adjacency Matrix-Coded DE for TSP -- 3.1 Population Initializing. , 3.2 Procedure of RAMDE -- 4 Experimental Studies -- 4.1 Comparisons with Other EAs Using Different Data Representation -- 4.2 Analysis of the Convergent Characteristics of RAMDE -- 5 Conclusion -- References -- A Hybrid IWO Algorithm Based on Lévy Flight -- 1 Introduction -- 2 Preliminary Study -- 2.1 Invasive Weed Optimization -- 2.2 Invasive Weed Optimization -- 3 Hybrid IWO Algorithm Based on Lévy Flights -- 4 Simulation Studies -- 4.1 Test Functions -- 4.2 Test Functions -- 5 Conclusion -- References -- Evolutionary Process: Parallelism Analysis of Differential Evolution Algorithm Based on Graph Theory -- 1 Introduction -- 2 Classical Differential Evolution Algorithm -- 2.1 Initialization -- 2.2 The Mutation Strategy -- 2.3 The Crossover Operation -- 2.4 The Selection Operation -- 3 Parallelism Analysis Based on Graph Theory -- 3.1 Graph Theory Description of Differential Evolution -- 3.2 Parallel Characteristic Analysis for Differential Evolution -- 4 Experiment and Results -- 5 Conclusion -- References -- A Mean Shift Assisted Differential Evolution Algorithm -- 1 Introduction -- 2 Proposed Algorithm -- 2.1 Algorithm Description -- 2.2 Search Operator Based on Mean Shift -- 3 Experimental Results -- 3.1 Test Instances and Parameter Settings -- 3.2 Experimental Results and Analysis -- 3.3 Sensitivity to Kernel Parameters -- 4 Conclusion -- References -- Quantum-Behaved Particle Swarm Optimization Using MapReduce -- 1 Introduction -- 2 The MRQPSO Algorithm -- 2.1 MRQPSO Map Function -- 2.2 MRQPSO Reduce Function -- 3 Experiment Result and Analysis -- 3.1 Compared Algorithms, Parameter Settings and Environment -- 3.2 Comparison with QPSO -- 4 Conclusion -- References -- Dynamic Fitness Landscape Analysis on Differential Evolution Algorithm -- 1 Introduction -- 2 Fitness Landscape Analysis -- 2.1 Dynamic Severity -- 2.2 Ruggedness. , 2.3 Success Rate.